R-universe search: trajectories

jimmcl

trajr:Animal Trajectory Analysis

A toolbox to assist with statistical analysis of animal trajectories. It provides simple access to algorithms for calculating and assessing a variety of characteristics such as speed and acceleration, as well as multiple measures of straightness or tortuosity. Some support is provided for 3-dimensional trajectories. McLean & Skowron Volponi (2018) <doi:10.1111/eth.12739>.

Maintained by Jim McLean. Last updated 8 months ago.

135.2 match 27 stars 7.69 score 151 scripts

edzer

trajectories:Classes and Methods for Trajectory Data

Classes and methods for trajectory data, with support for nesting individual Track objects in track sets (Tracks) and track sets for different entities in collections of Tracks. Methods include selection, generalization, aggregation, intersection, simulation, and plotting.

Maintained by Edzer Pebesma. Last updated 7 months ago.

83.7 match 31 stars 7.25 score 76 scripts 1 dependents

dynverse

dynwrap:Representing and Inferring Single-Cell Trajectories

Provides functionality to infer trajectories from single-cell data, represent them into a common format, and adapt them. Other biological information can also be added, such as cellular grouping, RNA velocity and annotation. Saelens et al. (2019) <doi:10.1038/s41587-019-0071-9>.

Maintained by Robrecht Cannoodt. Last updated 2 years ago.

trajectory-inference

66.8 match 16 stars 7.48 score 159 scripts 1 dependents

pascalkieslich

mousetrap:Process and Analyze Mouse-Tracking Data

Mouse-tracking, the analysis of mouse movements in computerized experiments, is a method that is becoming increasingly popular in the cognitive sciences. The mousetrap package offers functions for importing, preprocessing, analyzing, aggregating, and visualizing mouse-tracking data. An introduction into mouse-tracking analyses using mousetrap can be found in Wulff, Kieslich, Henninger, Haslbeck, & Schulte-Mecklenbeck (2023) <doi:10.31234/osf.io/v685r> (preprint: <https://osf.io/preprints/psyarxiv/v685r>).

Maintained by Pascal J. Kieslich. Last updated 1 years ago.

analysis clustering mouse-tracking visualization cpp

51.3 match 46 stars 6.68 score 124 scripts

clementcalenge

adehabitatLT:Analysis of Animal Movements

A collection of tools for the analysis of animal movements.

Maintained by Clement Calenge. Last updated 6 months ago.

34.0 match 6 stars 8.60 score 370 scripts 12 dependents

ropensci

pathviewr:Wrangle, Analyze, and Visualize Animal Movement Data

Tools to import, clean, and visualize movement data, particularly from motion capture systems such as Optitrack's 'Motive', the Straw Lab's 'Flydra', or from other sources. We provide functions to remove artifacts, standardize tunnel position and tunnel axes, select a region of interest, isolate specific trajectories, fill gaps in trajectory data, and calculate 3D and per-axis velocity. For experiments of visual guidance, we also provide functions that use subject position to estimate perception of visual stimuli.

Maintained by Vikram B. Baliga. Last updated 2 years ago.

animal-movement flydra motion movement-data optitrack trajectories trajectory-analysis visual-guidance visual-perception

40.3 match 8 stars 6.56 score 102 scripts

philips-software

latrend:A Framework for Clustering Longitudinal Data

A framework for clustering longitudinal datasets in a standardized way. The package provides an interface to existing R packages for clustering longitudinal univariate trajectories, facilitating reproducible and transparent analyses. Additionally, standard tools are provided to support cluster analyses, including repeated estimation, model validation, and model assessment. The interface enables users to compare results between methods, and to implement and evaluate new methods with ease. The 'akmedoids' package is available from <https://github.com/MAnalytics/akmedoids>.

Maintained by Niek Den Teuling. Last updated 2 months ago.

cluster-analysis clustering-evaluation clustering-methods data-science longitudinal-clustering longitudinal-data mixture-models time-series-analysis

35.3 match 30 stars 6.77 score 26 scripts

stewid

SimInf:A Framework for Data-Driven Stochastic Disease Spread Simulations

Provides an efficient and very flexible framework to conduct data-driven epidemiological modeling in realistic large scale disease spread simulations. The framework integrates infection dynamics in subpopulations as continuous-time Markov chains using the Gillespie stochastic simulation algorithm and incorporates available data such as births, deaths and movements as scheduled events at predefined time-points. Using C code for the numerical solvers and 'OpenMP' (if available) to divide work over multiple processors ensures high performance when simulating a sample outcome. One of our design goals was to make the package extendable and enable usage of the numerical solvers from other R extension packages in order to facilitate complex epidemiological research. The package contains template models and can be extended with user-defined models. For more details see the paper by Widgren, Bauer, Eriksson and Engblom (2019) <doi:10.18637/jss.v091.i12>. The package also provides functionality to fit models to time series data using the Approximate Bayesian Computation Sequential Monte Carlo ('ABC-SMC') algorithm of Toni and others (2009) <doi:10.1098/rsif.2008.0172>.

Maintained by Stefan Widgren. Last updated 6 days ago.

data-driven epidemiology high-performance-computing markov-chain mathematical-modelling gsl openmp

23.4 match 35 stars 10.09 score 227 scripts

r-simmer

simmer:Discrete-Event Simulation for R

A process-oriented and trajectory-based Discrete-Event Simulation (DES) package for R. It is designed as a generic yet powerful framework. The architecture encloses a robust and fast simulation core written in 'C++' with automatic monitoring capabilities. It provides a rich and flexible R API that revolves around the concept of trajectory, a common path in the simulation model for entities of the same type. Documentation about 'simmer' is provided by several vignettes included in this package, via the paper by Ucar, Smeets & Azcorra (2019, <doi:10.18637/jss.v090.i02>), and the paper by Ucar, Hernández, Serrano & Azcorra (2018, <doi:10.1109/MCOM.2018.1700960>); see 'citation("simmer")' for details.

Maintained by Iñaki Ucar. Last updated 6 months ago.

discrete-event simulation cpp

20.2 match 223 stars 11.47 score 440 scripts 6 dependents

cbracis

recurse:Computes Revisitation Metrics for Trajectory Data

Computes revisitation metrics for trajectory data, such as the number of revisitations for each location as well as the time spent for that visit and the time since the previous visit. Also includes functions to plot data.

Maintained by Chloe Bracis. Last updated 8 months ago.

cpp

31.1 match 10 stars 6.24 score 43 scripts

munterfi

eRTG3D:Empirically Informed Random Trajectory Generation in 3-D

Creates realistic random trajectories in a 3-D space between two given fix points, so-called conditional empirical random walks (CERWs). The trajectory generation is based on empirical distribution functions extracted from observed trajectories (training data) and thus reflects the geometrical movement characteristics of the mover. A digital elevation model (DEM), representing the Earth's surface, and a background layer of probabilities (e.g. food sources, uplift potential, waterbodies, etc.) can be used to influence the trajectories. Unterfinger M (2018). "3-D Trajectory Simulation in Movement Ecology: Conditional Empirical Random Walk". Master's thesis, University of Zurich. <https://www.geo.uzh.ch/dam/jcr:6194e41e-055c-4635-9807-53c5a54a3be7/MasterThesis_Unterfinger_2018.pdf>. Technitis G, Weibel R, Kranstauber B, Safi K (2016). "An algorithm for empirically informed random trajectory generation between two endpoints". GIScience 2016: Ninth International Conference on Geographic Information Science, 9, online. <doi:10.5167/uzh-130652>.

Maintained by Merlin Unterfinger. Last updated 3 years ago.

3d birds conditional-empirical-random-walk gliding-and-soaring machine-learning movement-ecology random-trajectory-generator random-walk simulation trajectory-generation

32.6 match 6 stars 5.71 score 19 scripts

bioc

slingshot:Tools for ordering single-cell sequencing

Provides functions for inferring continuous, branching lineage structures in low-dimensional data. Slingshot was designed to model developmental trajectories in single-cell RNA sequencing data and serve as a component in an analysis pipeline after dimensionality reduction and clustering. It is flexible enough to handle arbitrarily many branching events and allows for the incorporation of prior knowledge through supervised graph construction.

Maintained by Kelly Street. Last updated 5 months ago.

clustering differentialexpression geneexpression rnaseq sequencing software singlecell transcriptomics visualization

14.3 match 283 stars 12.01 score 1.0k scripts 4 dependents

bioc

CellTrails:Reconstruction, visualization and analysis of branching trajectories

CellTrails is an unsupervised algorithm for the de novo chronological ordering, visualization and analysis of single-cell expression data. CellTrails makes use of a geometrically motivated concept of lower-dimensional manifold learning, which exhibits a multitude of virtues that counteract intrinsic noise of single cell data caused by drop-outs, technical variance, and redundancy of predictive variables. CellTrails enables the reconstruction of branching trajectories and provides an intuitive graphical representation of expression patterns along all branches simultaneously. It allows the user to define and infer the expression dynamics of individual and multiple pathways towards distinct phenotypes.

Maintained by Daniel Ellwanger. Last updated 5 months ago.

immunooncology clustering datarepresentation differentialexpression dimensionreduction geneexpression sequencing singlecell software timecourse

38.8 match 4.00 score 7 scripts

rcannood

SCORPIUS:Inferring Developmental Chronologies from Single-Cell RNA Sequencing Data

An accurate and easy tool for performing linear trajectory inference on single cells using single-cell RNA sequencing data. In addition, 'SCORPIUS' provides functions for discovering the most important genes with respect to the reconstructed trajectory, as well as nice visualisation tools. Cannoodt et al. (2016) <doi:10.1101/079509>.

Maintained by Robrecht Cannoodt. Last updated 2 years ago.

18.8 match 59 stars 8.17 score 126 scripts

bart1

move2:Processing and Analysing Animal Trajectories

Tools to handle, manipulate and explore trajectory data, with an emphasis on data from tracked animals. The package is designed to support large studies with several million location records and keep track of units where possible. Data import directly from 'movebank' <https://www.movebank.org/cms/movebank-main> and files is facilitated.

Maintained by Bart Kranstauber. Last updated 1 months ago.

18.5 match 7.51 score 169 scripts 1 dependents

bioc

deltaGseg:deltaGseg

Identifying distinct subpopulations through multiscale time series analysis

Maintained by Diana Low. Last updated 5 months ago.

proteomics timecourse visualization clustering

41.1 match 3.30 score 2 scripts

mspinillos

ecoregime:Analysis of Ecological Dynamic Regimes

A toolbox for implementing the Ecological Dynamic Regime framework (Sánchez-Pinillos et al., 2023 <doi:10.1002/ecm.1589>) to characterize and compare groups of ecological trajectories in multidimensional spaces defined by state variables. The package includes the RETRA-EDR algorithm to identify representative trajectories, functions to generate, summarize, and visualize representative trajectories, and several metrics to quantify the distribution and heterogeneity of trajectories in an ecological dynamic regime and quantify the dissimilarity between two or more ecological dynamic regimes. The package also includes a set of functions to assess ecological resilience based on ecological dynamic regimes (Sánchez-Pinillos et al., 2024 <doi:10.1016/j.biocon.2023.110409>).

Maintained by Martina Sánchez-Pinillos. Last updated 11 months ago.

25.4 match 7 stars 5.32 score 8 scripts

stan-dev

rstanarm:Bayesian Applied Regression Modeling via Stan

Estimates previously compiled regression models using the 'rstan' package, which provides the R interface to the Stan C++ library for Bayesian estimation. Users specify models via the customary R syntax with a formula and data.frame plus some additional arguments for priors.

Maintained by Ben Goodrich. Last updated 9 months ago.

bayesian bayesian-data-analysis bayesian-inference bayesian-methods bayesian-statistics multilevel-models rstan rstanarm stan statistical-modeling cpp

8.1 match 393 stars 15.68 score 5.0k scripts 13 dependents

emf-creaf

ecotraj:Ecological Trajectory Analysis

Assists ecologists in the analysis of temporal changes of ecosystems, defined as trajectories on a chosen multivariate space, by providing a set of trajectory metrics and visual representations [De Caceres et al. (2019) <doi:10.1002/ecm.1350>; and Sturbois et al. (2021) <doi:10.1016/j.ecolmodel.2020.109400>]. Includes functions to estimate metrics for individual trajectories (length, directionality, angles, ...) as well as metrics to relate pairs of trajectories (dissimilarity and convergence). Functions are also provided to estimate the ecological quality of ecosystem with respect to reference conditions [Sturbois et al. (2023) <doi:10.1002/ecs2.4726>].

Maintained by Miquel De Cáceres. Last updated 20 days ago.

cpp

23.9 match 4 stars 5.21 score 21 scripts 1 dependents

mlcollyer

RRPP:Linear Model Evaluation with Randomized Residuals in a Permutation Procedure

Linear model calculations are made for many random versions of data. Using residual randomization in a permutation procedure, sums of squares are calculated over many permutations to generate empirical probability distributions for evaluating model effects. Additionally, coefficients, statistics, fitted values, and residuals generated over many permutations can be used for various procedures including pairwise tests, prediction, classification, and model comparison. This package should provide most tools one could need for the analysis of high-dimensional data, especially in ecology and evolutionary biology, but certainly other fields, as well.

Maintained by Michael Collyer. Last updated 27 days ago.

12.2 match 4 stars 9.84 score 173 scripts 7 dependents

canmod

macpan2:Fast and Flexible Compartmental Modelling

Fast and flexible compartmental modelling with Template Model Builder.

Maintained by Steve Walker. Last updated 6 hours ago.

compartmental-models epidemiology forecasting mixed-effects model-fitting optimization simulation simulation-modeling cpp

13.0 match 4 stars 8.90 score 246 scripts 1 dependents

smac-group

navigation:Analyze the Impact of Sensor Error Modelling on Navigation Performance

Implements the framework presented in Cucci, D. A., Voirol, L., Khaghani, M. and Guerrier, S. (2023) <doi:10.1109/TIM.2023.3267360> which allows to analyze the impact of sensor error modeling on the performance of integrated navigation (sensor fusion) based on inertial measurement unit (IMU), Global Positioning System (GPS), and barometer data. The framework relies on Monte Carlo simulations in which a Vanilla Extended Kalman filter is coupled with realistic and user-configurable noise generation mechanisms to recover a reference trajectory from noisy measurements. The evaluation of several statistical metrics of the solution, aggregated over hundreds of simulated realizations, provides reasonable estimates of the expected performances of the system in real-world conditions.

Maintained by Lionel Voirol. Last updated 2 years ago.

openblas cpp

22.7 match 5 stars 4.95 score 18 scripts

kingaa

pomp:Statistical Inference for Partially Observed Markov Processes

Tools for data analysis with partially observed Markov process (POMP) models (also known as stochastic dynamical systems, hidden Markov models, and nonlinear, non-Gaussian, state-space models). The package provides facilities for implementing POMP models, simulating them, and fitting them to time series data by a variety of frequentist and Bayesian methods. It is also a versatile platform for implementation of inference methods for general POMP models.

Maintained by Aaron A. King. Last updated 1 months ago.

abc b-spline differential-equations dynamical-systems iterated-filtering likelihood likelihood-free markov-chain-monte-carlo markov-model mathematical-modelling measurement-error particle-filter sequential-monte-carlo simulation-based-inference sobol-sequence state-space statistical-inference stochastic-processes time-series openblas

9.5 match 115 stars 11.81 score 1.3k scripts 4 dependents

tchouangue

traj:Trajectory Analysis

Implements the three-step procedure proposed by Leffondree et al. (2004) to identify clusters of individual longitudinal trajectories. The procedure involves (1) calculating 24 measures describing the features of the trajectories; (2) using factor analysis to select a subset of the 24 measures and (3) using cluster analysis to identify clusters of trajectories, and classify each individual trajectory in one of the clusters.

Maintained by Gillis Delmas TCHOUANGUE DINKOU. Last updated 2 years ago.

18.3 match 2 stars 5.28 score 21 scripts

bioc

cellmigRation:Track Cells, Analyze Cell Trajectories and Compute Migration Statistics

Import TIFF images of fluorescently labeled cells, and track cell movements over time. Parallelization is supported for image processing and for fast computation of cell trajectories. In-depth analysis of cell trajectories is enabled by 15 trajectory analysis functions.

Maintained by Waldir Leoncio. Last updated 5 months ago.

cellbiology datarepresentation dataimport bioconductor-package cell-tracking shiny trajectory-analysis

20.6 match 4.60 score 4 scripts

openair-project

openair:Tools for the Analysis of Air Pollution Data

Tools to analyse, interpret and understand air pollution data. Data are typically regular time series and air quality measurement, meteorological data and dispersion model output can be analysed. The package is described in Carslaw and Ropkins (2012, <doi:10.1016/j.envsoft.2011.09.008>) and subsequent papers.

Maintained by David Carslaw. Last updated 26 days ago.

air-quality air-quality-data meteorology openair cpp

7.3 match 311 stars 12.91 score 1.2k scripts 12 dependents

mablab

sftrack:Modern Classes for Tracking and Movement Data

Modern classes for tracking and movement data, building on 'sf' spatial infrastructure, and early theoretical work from Turchin (1998, ISBN: 9780878938476), and Calenge et al. (2009) <doi:10.1016/j.ecoinf.2008.10.002>. Tracking data are series of locations with at least 2-dimensional spatial coordinates (x,y), a time index (t), and individual identification (id) of the object being monitored; movement data are made of trajectories, i.e. the line representation of the path, composed by steps (the straight-line segments connecting successive locations). 'sftrack' is designed to handle movement of both living organisms and inanimate objects.

Maintained by Mathieu Basille. Last updated 2 years ago.

movement tracking-data trajectory

14.4 match 53 stars 6.42 score 5 scripts

asardaes

dtwclust:Time Series Clustering Along with Optimizations for the Dynamic Time Warping Distance

Time series clustering along with optimized techniques related to the Dynamic Time Warping distance and its corresponding lower bounds. Implementations of partitional, hierarchical, fuzzy, k-Shape and TADPole clustering are available. Functionality can be easily extended with custom distance measures and centroid definitions. Implementations of DTW barycenter averaging, a distance based on global alignment kernels, and the soft-DTW distance and centroid routines are also provided. All included distance functions have custom loops optimized for the calculation of cross-distance matrices, including parallelization support. Several cluster validity indices are included.

Maintained by Alexis Sarda. Last updated 8 months ago.

clustering dtw time-series openblas cpp

7.2 match 261 stars 12.39 score 406 scripts 14 dependents

bioc

flowcatchR:Tools to analyze in vivo microscopy imaging data focused on tracking flowing blood cells

flowcatchR is a set of tools to analyze in vivo microscopy imaging data, focused on tracking flowing blood cells. It guides the steps from segmentation to calculation of features, filtering out particles not of interest, providing also a set of utilities to help checking the quality of the performed operations (e.g. how good the segmentation was). It allows investigating the issue of tracking flowing cells such as in blood vessels, to categorize the particles in flowing, rolling and adherent. This classification is applied in the study of phenomena such as hemostasis and study of thrombosis development. Moreover, flowcatchR presents an integrated workflow solution, based on the integration with a Shiny App and Jupyter notebooks, which is delivered alongside the package, and can enable fully reproducible bioimage analysis in the R environment.

Maintained by Federico Marini. Last updated 3 months ago.

software visualization cellbiology classification infrastructure gui shinyapps bioconductor fluorescence microscopy particles tracking

15.4 match 4 stars 5.62 score 8 scripts

awesometothemax

SimilarityMeasures:Trajectory Similarity Measures

Functions to run and assist four different similarity measures. The similarity measures included are: longest common subsequence (LCSS), Frechet distance, edit distance and dynamic time warping (DTW). Each of these similarity measures can be calculated from two n-dimensional trajectories, both in matrix form.

Maintained by Kevin Toohey. Last updated 10 years ago.

22.9 match 2 stars 3.61 score 34 scripts 12 dependents

openair-project

openairmaps:Create Maps of Air Pollution Data

Combine the air quality data analysis methods of 'openair' with the JavaScript 'Leaflet' (<https://leafletjs.com/>) library. Functionality includes plotting site maps, "directional analysis" figures such as polar plots, and air mass trajectories.

Maintained by Jack Davison. Last updated 2 days ago.

openair

13.4 match 21 stars 6.04 score 47 scripts

bart1

move:Visualizing and Analyzing Animal Track Data

Contains functions to access movement data stored in 'movebank.org' as well as tools to visualize and statistically analyze animal movement data, among others functions to calculate dynamic Brownian Bridge Movement Models. Move helps addressing movement ecology questions.

Maintained by Bart Kranstauber. Last updated 4 months ago.

cpp

9.1 match 8.74 score 690 scripts 3 dependents

projectmosaic

mosaicCalc:R-Language Based Calculus Operations for Teaching

Software to support the introductory *MOSAIC Calculus* textbook <https://www.mosaic-web.org/MOSAIC-Calculus/>), one of many data- and modeling-oriented educational resources developed by Project MOSAIC (<https://www.mosaic-web.org/>). Provides symbolic and numerical differentiation and integration, as well as support for applied linear algebra (for data science), and differential equations/dynamics. Includes grammar-of-graphics-based functions for drawing vector fields, trajectories, etc. The software is suitable for general use, but intended mainly for teaching calculus.

Maintained by Daniel Kaplan. Last updated 21 days ago.

8.4 match 13 stars 8.68 score 546 scripts

go-ski

clustra:Clustering Longitudinal Trajectories

Clusters longitudinal trajectories over time (can be unequally spaced, unequal length time series and/or partially overlapping series) on a common time axis. Performs k-means clustering on a single continuous variable measured over time, where each mean is defined by a thin plate spline fit to all points in a cluster. Distance is MSE across trajectory points to cluster spline. Provides graphs of derived cluster splines, silhouette plots, and Adjusted Rand Index evaluations of the number of clusters. Scales well to large data with multicore parallelism available to speed computation.

Maintained by George Ostrouchov. Last updated 3 months ago.

15.9 match 4.48 score 6 scripts

hanase

bayesTFR:Bayesian Fertility Projection

Making probabilistic projections of total fertility rate for all countries of the world, using a Bayesian hierarchical model <doi:10.1007/s13524-011-0040-5> <doi:10.18637/jss.v106.i08>. Subnational probabilistic projections are also supported <doi:10.4054/DemRes.2018.38.60>.

Maintained by Hana Sevcikova. Last updated 4 months ago.

20.8 match 2 stars 3.29 score 58 scripts 3 dependents

uniprjrc

fsdaR:Robust Data Analysis Through Monitoring and Dynamic Visualization

Provides interface to the 'MATLAB' toolbox 'Flexible Statistical Data Analysis (FSDA)' which is comprehensive and computationally efficient software package for robust statistics in regression, multivariate and categorical data analysis. The current R version implements tools for regression: (forward search, S- and MM-estimation, least trimmed squares (LTS) and least median of squares (LMS)), for multivariate analysis (forward search, S- and MM-estimation), for cluster analysis and cluster-wise regression. The distinctive feature of our package is the possibility of monitoring the statistics of interest as a function of breakdown point, efficiency or subset size, depending on the estimator. This is accompanied by a rich set of graphical features, such as dynamic brushing, linking, particularly useful for exploratory data analysis.

Maintained by Valentin Todorov. Last updated 1 years ago.

openjdk

12.2 match 5 stars 5.37 score 93 scripts

eliocamp

metR:Tools for Easier Analysis of Meteorological Fields

Many useful functions and extensions for dealing with meteorological data in the tidy data framework. Extends 'ggplot2' for better plotting of scalar and vector fields and provides commonly used analysis methods in the atmospheric sciences.

Maintained by Elio Campitelli. Last updated 22 days ago.

atmospheric-science ggplot2 visualization

5.3 match 144 stars 12.19 score 1000 scripts 22 dependents

bioc

dandelionR:Single-cell Immune Repertoire Trajectory Analysis in R

dandelionR is an R package for performing single-cell immune repertoire trajectory analysis, based on the original python implementation. It provides the necessary functions to interface with scRepertoire and a custom implementation of an absorbing Markov chain for pseudotime inference, inspired by the Palantir Python package.

Maintained by Kelvin Tuong. Last updated 15 days ago.

software immunooncology singlecell

10.8 match 8 stars 5.81 score 7 scripts

egarpor

sdetorus:Statistical Tools for Toroidal Diffusions

Implementation of statistical methods for the estimation of toroidal diffusions. Several diffusive models are provided, most of them belonging to the Langevin family of diffusions on the torus. Specifically, the wrapped normal and von Mises processes are included, which can be seen as toroidal analogues of the Ornstein-Uhlenbeck diffusion. A collection of methods for approximate maximum likelihood estimation, organized in four blocks, is given: (i) based on the exact transition probability density, obtained as the numerical solution to the Fokker-Plank equation; (ii) based on wrapped pseudo-likelihoods; (iii) based on specific analytic approximations by wrapped processes; (iv) based on maximum likelihood of the stationary densities. The package allows the replicability of the results in García-Portugués et al. (2019) <doi:10.1007/s11222-017-9790-2>.

Maintained by Eduardo García-Portugués. Last updated 1 years ago.

circular-statistics inference maximum-likelihood reproducible-research sde statistics toroidal-data openblas cpp

15.9 match 5 stars 3.88 score 9 scripts 1 dependents

awamaeva

trajmsm:Marginal Structural Models with Latent Class Growth Analysis of Treatment Trajectories

Implements marginal structural models combined with a latent class growth analysis framework for assessing the causal effect of treatment trajectories. Based on the approach described in "Marginal Structural Models with Latent Class Growth Analysis of Treatment Trajectories" Diop, A., Sirois, C., Guertin, J.R., Schnitzer, M.E., Candas, B., Cossette, B., Poirier, P., Brophy, J., Mésidor, M., Blais, C. and Hamel, D., (2023) <doi:10.1177/09622802231202384>.

Maintained by Awa Diop. Last updated 1 years ago.

g-computation inverse-probability-weights marginal-structural-models tmle trajectory-analysis

16.9 match 5 stars 3.40 score

matthieu-bruneaux

isotracer:Isotopic Tracer Analysis Using MCMC

Implements Bayesian models to analyze data from tracer addition experiments. The implemented method was originally described in the article "A New Method to Reconstruct Quantitative Food Webs and Nutrient Flows from Isotope Tracer Addition Experiments" by López-Sepulcre et al. (2020) <doi:10.1086/708546>.

Maintained by Matthieu Bruneaux. Last updated 4 months ago.

cpp

9.7 match 5.92 score 60 scripts

hanase

bayesPop:Probabilistic Population Projection

Generating population projections for all countries of the world using several probabilistic components, such as total fertility rate and life expectancy (Raftery et al., 2012 <doi:10.1073/pnas.1211452109>).

Maintained by Hana Sevcikova. Last updated 24 days ago.

26.3 match 2.15 score 44 scripts

centerforassessment

SGP:Student Growth Percentiles & Percentile Growth Trajectories

An analytic framework for the calculation of norm- and criterion-referenced academic growth estimates using large scale, longitudinal education assessment data as developed in Betebenner (2009) <doi:10.1111/j.1745-3992.2009.00161.x>.

Maintained by Damian W. Betebenner. Last updated 2 months ago.

percentile-growth-projections quantile-regression sgp sgp-analyses student-growth-percentiles student-growth-projections

5.8 match 20 stars 9.69 score 88 scripts

bioc

tradeSeq:trajectory-based differential expression analysis for sequencing data

tradeSeq provides a flexible method for fitting regression models that can be used to find genes that are differentially expressed along one or multiple lineages in a trajectory. Based on the fitted models, it uses a variety of tests suited to answer different questions of interest, e.g. the discovery of genes for which expression is associated with pseudotime, or which are differentially expressed (in a specific region) along the trajectory. It fits a negative binomial generalized additive model (GAM) for each gene, and performs inference on the parameters of the GAM.

Maintained by Hector Roux de Bezieux. Last updated 5 months ago.

clustering regression timecourse differentialexpression geneexpression rnaseq sequencing software singlecell transcriptomics multiplecomparison visualization

5.1 match 247 stars 10.06 score 440 scripts

d-score

dscore:D-Score for Child Development

The D-score summarizes the child's performance on a set of milestones into a single number. The package implements four Rasch model keys to convert milestone scores into a D-score. It provides tools to calculate the D-score and its precision from the child's milestone scores, to convert the D-score into the Development-for-Age Z-score (DAZ) using age-conditional references, and to map milestone names into a generic 9-position item naming convention.

Maintained by Stef van Buuren. Last updated 7 months ago.

child-development d-score daz developmental-trajectories growth-charts rasch-model cpp

7.5 match 8 stars 6.89 score 40 scripts

hanase

bayesLife:Bayesian Projection of Life Expectancy

Making probabilistic projections of life expectancy for all countries of the world, using a Bayesian hierarchical model <doi:10.1007/s13524-012-0193-x>. Subnational projections are also supported.

Maintained by Hana Sevcikova. Last updated 3 months ago.

20.6 match 1 stars 2.45 score 41 scripts 1 dependents

adwolfer

santaR:Short Asynchronous Time-Series Analysis

A graphical and automated pipeline for the analysis of short time-series in R ('santaR'). This approach is designed to accommodate asynchronous time sampling (i.e. different time points for different individuals), inter-individual variability, noisy measurements and large numbers of variables. Based on a smoothing splines functional model, 'santaR' is able to detect variables highlighting significantly different temporal trajectories between study groups. Designed initially for metabolic phenotyping, 'santaR' is also suited for other Systems Biology disciplines. Command line and graphical analysis (via a 'shiny' application) enable fast and parallel automated analysis and reporting, intuitive visualisation and comprehensive plotting options for non-specialist users.

Maintained by Arnaud Wolfer. Last updated 1 years ago.

pcamethods (>= 1.92.0)

7.8 match 11 stars 6.44 score 63 scripts

mjg211

phaseR:Phase Plane Analysis of One- And Two-Dimensional Autonomous ODE Systems

Performs a qualitative analysis of one- and two-dimensional autonomous ordinary differential equation systems, using phase plane methods. Programs are available to identify and classify equilibrium points, plot the direction field, and plot trajectories for multiple initial conditions. In the one-dimensional case, a program is also available to plot the phase portrait. Whilst in the two-dimensional case, programs are additionally available to plot nullclines and stable/unstable manifolds of saddle points. Many example systems are provided for the user. For further details can be found in Grayling (2014) <doi:10.32614/RJ-2014-023>.

Maintained by Michael J Grayling. Last updated 3 years ago.

biological-modeling differential-equations dynamical-systems ecological-modelling lotka-volterra manifolds modeling-dynamic-systems morris-lecar perturbation-analysis phase-plane sir-model species-interactions van-der-pol

7.4 match 15 stars 6.63 score 94 scripts 1 dependents

bioc

monocle:Clustering, differential expression, and trajectory analysis for single- cell RNA-Seq

Monocle performs differential expression and time-series analysis for single-cell expression experiments. It orders individual cells according to progress through a biological process, without knowing ahead of time which genes define progress through that process. Monocle also performs differential expression analysis, clustering, visualization, and other useful tasks on single cell expression data. It is designed to work with RNA-Seq and qPCR data, but could be used with other types as well.

Maintained by Cole Trapnell. Last updated 5 months ago.

immunooncology sequencing rnaseq geneexpression differentialexpression infrastructure dataimport datarepresentation visualization clustering multiplecomparison qualitycontrol cpp

5.5 match 8.89 score 1.6k scripts 2 dependents

bioc

phenopath:Genomic trajectories with heterogeneous genetic and environmental backgrounds

PhenoPath infers genomic trajectories (pseudotimes) in the presence of heterogeneous genetic and environmental backgrounds and tests for interactions between them.

Maintained by Kieran Campbell. Last updated 5 months ago.

immunooncology rnaseq geneexpression bayesian singlecell principalcomponent cpp

10.1 match 4.63 score 43 scripts

marshalllab

MGDrivE2:Mosquito Gene Drive Explorer 2

A simulation modeling framework which significantly extends capabilities from the 'MGDrivE' simulation package via a new mathematical and computational framework based on stochastic Petri nets. For more information about 'MGDrivE', see our publication: <https://besjournals.onlinelibrary.wiley.com/doi/full/10.1111/2041-210X.13318>. Some of the notable capabilities of 'MGDrivE2' include: incorporation of human populations, epidemiological dynamics, time-varying parameters, and a continuous-time simulation framework with various sampling algorithms for both deterministic and stochastic interpretations. 'MGDrivE2' relies on the genetic inheritance structures provided in package 'MGDrivE', so we suggest installing that package initially.

Maintained by Sean L. Wu. Last updated 4 years ago.

7.3 match 6 stars 6.33 score 30 scripts

traitecoevo

litterfitter:Fit a Collection of Curves to Single Cohort Decomposition Data

There is a long tradition of studying the flux of carbon from the biosphere to the atmosphere by following a particular cohort of litter (wood, leaves, roots, or other organic material) through time. The resulting data are mass remaining and time. A variety of functional forms may be used to fit the resulting data. Some work better empirically. Some are better connected to a process-based understanding. Some have a small number of free parameters; others have more. This package matches decomposition data to a family of these curves using likelihood--based fitting. This package is based on published research by Cornwell & Weedon (2013) <doi:10.1111/2041-210X.12138>.

Maintained by Will Cornwell. Last updated 2 years ago.

8.9 match 5 stars 5.05 score 15 scripts

tyee001

VGAM:Vector Generalized Linear and Additive Models

An implementation of about 6 major classes of statistical regression models. The central algorithm is Fisher scoring and iterative reweighted least squares. At the heart of this package are the vector generalized linear and additive model (VGLM/VGAM) classes. VGLMs can be loosely thought of as multivariate GLMs. VGAMs are data-driven VGLMs that use smoothing. The book "Vector Generalized Linear and Additive Models: With an Implementation in R" (Yee, 2015) <DOI:10.1007/978-1-4939-2818-7> gives details of the statistical framework and the package. Currently only fixed-effects models are implemented. Many (100+) models and distributions are estimated by maximum likelihood estimation (MLE) or penalized MLE. The other classes are RR-VGLMs (reduced-rank VGLMs), quadratic RR-VGLMs, doubly constrained RR-VGLMs, quadratic RR-VGLMs, reduced-rank VGAMs, RCIMs (row-column interaction models)---these classes perform constrained and unconstrained quadratic ordination (CQO/UQO) models in ecology, as well as constrained additive ordination (CAO). Hauck-Donner effect detection is implemented. Note that these functions are subject to change; see the NEWS and ChangeLog files for latest changes.

Maintained by Thomas Yee. Last updated 1 months ago.

fortran

4.1 match 10 stars 10.67 score 3.6k scripts 169 dependents

leef-uzh

bemovi.LEEF:BEMOVI, software for extracting BEhaviour and MOrphology from VIdeos. This version is adapted for LEEF-UZH

An R and ImageJ based work flow to automatically measure behaviour and morphology from videos. Moving individuals are identified by background subtraction, morphology extracted, and trajectories assembled through time from coordinate data. Abundance, morphology and behaviour can be summarized based on trajectory data.

Maintained by Rainer M Krug. Last updated 1 years ago.

13.0 match 3.32 score 2 dependents

rmi-pacta

r2dii.plot:Visualize the Climate Scenario Alignment of a Financial Portfolio

Create plots to visualize the alignment of a corporate lending financial portfolio to climate change scenarios based on climate indicators (production and emission intensities) across key climate relevant sectors of the 'PACTA' methodology (Paris Agreement Capital Transition Assessment; <https://www.transitionmonitor.com/>). Financial institutions use 'PACTA' to study how their capital allocation decisions align with climate change mitigation goals.

Maintained by Monika Furdyna. Last updated 14 days ago.

5.8 match 8 stars 7.31 score 33 scripts 5 dependents

jonesor

Rage:Life History Metrics from Matrix Population Models

Functions for calculating life history metrics using matrix population models ('MPMs'). Described in Jones et al. (2021) <doi:10.1101/2021.04.26.441330>.

Maintained by Owen Jones. Last updated 3 months ago.

5.1 match 11 stars 8.17 score 62 scripts 1 dependents

rmi-pacta

pacta.multi.loanbook:Run 'PACTA' on Multiple Loan Books Easily

Run Paris Agreement Capital Transition Assessment ('PACTA') analyses on multiple loan books in a structured way. Provides access to standard 'PACTA' metrics and additional 'PACTA'-related metrics for multiple loan books. Results take the form of 'csv' files and plots and are exported to user-specified project paths.

Maintained by Jacob Kastl. Last updated 3 days ago.

climate-change pacta pactaverse sustainable-finance

6.4 match 6.48 score 4 scripts

traminer

TraMineR:Trajectory Miner: a Sequence Analysis Toolkit

Set of sequence analysis tools for manipulating, describing and rendering categorical sequences, and more generally mining sequence data in the field of social sciences. Although this sequence analysis package is primarily intended for state or event sequences that describe time use or life courses such as family formation histories or professional careers, its features also apply to many other kinds of categorical sequence data. It accepts many different sequence representations as input and provides tools for converting sequences from one format to another. It offers several functions for describing and rendering sequences, for computing distances between sequences with different metrics (among which optimal matching), original dissimilarity-based analysis tools, and functions for extracting the most frequent event subsequences and identifying the most discriminating ones among them. A user's guide can be found on the TraMineR web page.

Maintained by Gilbert Ritschard. Last updated 3 months ago.

cpp

4.8 match 11 stars 8.24 score 534 scripts 13 dependents

adeverse

adegraphics:An S4 Lattice-Based Package for the Representation of Multivariate Data

Graphical functionalities for the representation of multivariate data. It is a complete re-implementation of the functions available in the 'ade4' package.

Maintained by Aurélie Siberchicot. Last updated 8 months ago.

3.8 match 9 stars 10.37 score 386 scripts 6 dependents

bioc

miloR:Differential neighbourhood abundance testing on a graph

Milo performs single-cell differential abundance testing. Cell states are modelled as representative neighbourhoods on a nearest neighbour graph. Hypothesis testing is performed using either a negative bionomial generalized linear model or negative binomial generalized linear mixed model.

Maintained by Mike Morgan. Last updated 5 months ago.

singlecell multiplecomparison functionalgenomics software openblas cpp openmp

3.8 match 357 stars 10.49 score 340 scripts 1 dependents

bioc

TrajectoryUtils:Single-Cell Trajectory Analysis Utilities

Implements low-level utilities for single-cell trajectory analysis, primarily intended for re-use inside higher-level packages. Include a function to create a cluster-level minimum spanning tree and data structures to hold pseudotime inference results.

Maintained by Aaron Lun. Last updated 5 months ago.

geneexpression singlecell

6.6 match 5.91 score 16 scripts 9 dependents

psegaert

mrfDepth:Depth Measures in Multivariate, Regression and Functional Settings

Tools to compute depth measures and implementations of related tasks such as outlier detection, data exploration and classification of multivariate, regression and functional data.

Maintained by Jakob Raymaekers. Last updated 6 years ago.

fortran openblas cpp

7.8 match 3 stars 4.99 score 72 scripts 3 dependents

ebmtnprof

rties:Modeling Interpersonal Dynamics

The name of this package grew out of our research on temporal interpersonal emotion systems (TIES), hence 'rties'. It provides tools for using a set of models to investigate temporal processes in bivariate (e.g., dyadic) systems. The general approach is to model, one dyad at a time, the dynamics of a variable that is assessed repeatedly from both partners, extract the parameter estimates for each dyad, and then use those parameter estimates as input to a latent profile analysis to extract groups of dyads with qualitatively distinct dynamics. Finally, the profile memberships can be used to either predict, or be predicted by, another variable of interest. Currently, 2 models are supported: 1) inertia-coordination, and 2) a coupled-oscillator. Extended documentation is provided in vignettes. Theoretical background can be found in Butler (2011) <doi:10.1177/1088868311411164> and Butler & Barnard (2019) <doi:10.1097/PSY.0000000000000703>.

Maintained by Emily Butler. Last updated 3 years ago.

9.7 match 11 stars 3.94 score 16 scripts

modal-inria

cfda:Categorical Functional Data Analysis

Package for the analysis of categorical functional data. The main purpose is to compute an encoding (real functional variable) for each state <doi:10.3390/math9233074>. It also provides functions to perform basic statistical analysis on categorical functional data.

Maintained by Quentin Grimonprez. Last updated 2 months ago.

categorical-data functional-data-analysis hacktoberfest

8.3 match 4 stars 4.60 score 3 scripts

swarm-lab

trackdf:Data Frame Class for Tracking Data

Data frame class for storing collective movement data (e.g. fish schools, ungulate herds, baboon troops) collected from GPS trackers or computer vision tracking software.

Maintained by Simon Garnier. Last updated 2 years ago.

animal-behavior animal-behaviour gps gps-data

7.0 match 4 stars 5.42 score 11 scripts 1 dependents

bioc

switchde:Switch-like differential expression across single-cell trajectories

Inference and detection of switch-like differential expression across single-cell RNA-seq trajectories.

Maintained by Kieran Campbell. Last updated 5 months ago.

immunooncology software transcriptomics geneexpression rnaseq regression differentialexpression singlecell gene-expression genomics single-cell

6.1 match 19 stars 5.98 score 7 scripts

r-simmer

simmer.plot:Plotting Methods for 'simmer'

A set of plotting methods for 'simmer' trajectories and simulations.

Maintained by Iñaki Ucar. Last updated 5 months ago.

discrete-event plot simulation visualization

5.8 match 10 stars 6.18 score 152 scripts

fercol

BaSTA:Age-Specific Bayesian Survival Trajectory Analysis from Incomplete Census or Capture-Recapture/Recovery Data

Estimates survival and mortality with covariates from census or capture-recapture/recovery data in a Bayesian framework when many individuals are of unknown age. It includes tools for data checking, model diagnostics and outputs such as life-tables and plots, as described in Colchero, Jones, and Rebke (2012) <doi:10.1111/j.2041-210X.2012.00186.x> and Colchero et al. (2021) <doi:10.1038/s41467-021-23894-3>.

Maintained by Fernando Colchero. Last updated 2 months ago.

14.2 match 2.45 score 14 scripts

spatstat

spatstat.model:Parametric Statistical Modelling and Inference for the 'spatstat' Family

Functionality for parametric statistical modelling and inference for spatial data, mainly spatial point patterns, in the 'spatstat' family of packages. (Excludes analysis of spatial data on a linear network, which is covered by the separate package 'spatstat.linnet'.) Supports parametric modelling, formal statistical inference, and model validation. Parametric models include Poisson point processes, Cox point processes, Neyman-Scott cluster processes, Gibbs point processes and determinantal point processes. Models can be fitted to data using maximum likelihood, maximum pseudolikelihood, maximum composite likelihood and the method of minimum contrast. Fitted models can be simulated and predicted. Formal inference includes hypothesis tests (quadrat counting tests, Cressie-Read tests, Clark-Evans test, Berman test, Diggle-Cressie-Loosmore-Ford test, scan test, studentised permutation test, segregation test, ANOVA tests of fitted models, adjusted composite likelihood ratio test, envelope tests, Dao-Genton test, balanced independent two-stage test), confidence intervals for parameters, and prediction intervals for point counts. Model validation techniques include leverage, influence, partial residuals, added variable plots, diagnostic plots, pseudoscore residual plots, model compensators and Q-Q plots.

Maintained by Adrian Baddeley. Last updated 9 days ago.

analysis-of-variance cluster-process confidence-intervals cox-process determinantal-point-processes gibbs-process influence leverage model-diagnostics neyman-scott parameter-estimation poisson-process spatial-analysis spatial-modelling spatial-point-processes statistical-inference

3.8 match 5 stars 9.09 score 6 scripts 46 dependents

rmi-pacta

pacta.interactive.plot:What the Package Does (One Line, Title Case)

What the package does (one paragraph).

Maintained by CJ Yetman. Last updated 8 months ago.

d3 data-visualization interactive-visualizations pacta r2d3

6.6 match 2 stars 5.16 score 7 scripts 1 dependents

adeverse

ade4:Analysis of Ecological Data: Exploratory and Euclidean Methods in Environmental Sciences

Tools for multivariate data analysis. Several methods are provided for the analysis (i.e., ordination) of one-table (e.g., principal component analysis, correspondence analysis), two-table (e.g., coinertia analysis, redundancy analysis), three-table (e.g., RLQ analysis) and K-table (e.g., STATIS, multiple coinertia analysis). The philosophy of the package is described in Dray and Dufour (2007) <doi:10.18637/jss.v022.i04>.

Maintained by Aurélie Siberchicot. Last updated 14 days ago.

openblas cpp

2.3 match 39 stars 14.96 score 2.2k scripts 256 dependents

tengfei-emory

SLTCA:SLTCA: Scalable and Robust Latent Trajectory Class Analysis Using Artificial Likelihood

Conduct latent trajectory class analysis with longitudinal observations.

Maintained by Teng Fei. Last updated 4 years ago.

latent-class-analysis latent-trajectories

12.5 match 2.70 score

hayamizu-lab

treefit:The First Software for Quantitative Trajectory Inference

Perform two types of analysis: 1) checking the goodness-of-fit of tree models to your single-cell gene expression data; and 2) deciding which tree best fits your data.

Maintained by Kouhei Sutou. Last updated 1 months ago.

6.6 match 3 stars 4.95 score 1 scripts

lrioudurand

malt:Metropolis Adjusted Langevin Trajectories

Implements the sampling algorithm: Metropolis Adjusted Langevin Trajectories (Riou-Durand and Vogrinc 2022). Details available at: <arXiv:2202.13230>. The MALT algorithm is a robust extension of Hamiltonian Monte Carlo, for which robustness of tuning is enabled by a positive choice of damping parameter (a.k.a friction).

Maintained by Lionel Riou-Durand. Last updated 3 years ago.

9.6 match 3.30 score

gonchedanesh

TiPS:Trajectories and Phylogenies Simulator

Generates stochastic time series and genealogies associated with a population dynamics model. Times series are simulated using the Gillespie exact and approximate algorithms and a new algorithm we introduce that uses both approaches to optimize the time execution of the simulations. Genealogies are simulated from a trajectory using a backwards-in-time based approach. Methods are described in Danesh G et al (2022) <doi:10.1111/2041-210X.14038>.

Maintained by Gonche Danesh. Last updated 2 years ago.

cpp

9.6 match 3.30 score 8 scripts

growthcharts

brokenstick:Broken Stick Model for Irregular Longitudinal Data

Data on multiple individuals through time are often sampled at times that differ between persons. Irregular observation times can severely complicate the statistical analysis of the data. The broken stick model approximates each subject’s trajectory by one or more connected line segments. The times at which segments connect (breakpoints) are identical for all subjects and under control of the user. A well-fitting broken stick model effectively transforms individual measurements made at irregular times into regular trajectories with common observation times. Specification of the model requires three variables: time, measurement and subject. The model is a special case of the linear mixed model, with time as a linear B-spline and subject as the grouping factor. The main assumptions are: subjects are exchangeable, trajectories between consecutive breakpoints are straight, random effects follow a multivariate normal distribution, and unobserved data are missing at random. The package contains functions for fitting the broken stick model to data, for predicting curves in new data and for plotting broken stick estimates. The package supports two optimization methods, and includes options to structure the variance-covariance matrix of the random effects. The analyst may use the software to smooth growth curves by a series of connected straight lines, to align irregularly observed curves to a common time grid, to create synthetic curves at a user-specified set of breakpoints, to estimate the time-to-time correlation matrix and to predict future observations. See <doi:10.18637/jss.v106.i07> for additional documentation on background, methodology and applications.

Maintained by Stef van Buuren. Last updated 2 years ago.

b-spline growth-curves linear-mixed-models longitudinal-data

5.9 match 9 stars 5.33 score 12 scripts

stagedtrees

stagedtrees:Staged Event Trees

Creates and fits staged event tree probability models, which are probabilistic graphical models capable of representing asymmetric conditional independence statements for categorical variables. Includes functions to create, plot and fit staged event trees from data, as well as many efficient structure learning algorithms. References: Carli F, Leonelli M, Riccomagno E, Varando G (2022). <doi: 10.18637/jss.v102.i06>. Collazo R. A., Görgen C. and Smith J. Q. (2018, ISBN:9781498729604). Görgen C., Bigatti A., Riccomagno E. and Smith J. Q. (2018) <arXiv:1705.09457>. Thwaites P. A., Smith, J. Q. (2017) <arXiv:1510.00186>. Barclay L. M., Hutton J. L. and Smith J. Q. (2013) <doi:10.1016/j.ijar.2013.05.006>. Smith J. Q. and Anderson P. E. (2008) <doi:10.1016/j.artint.2007.05.004>.

Maintained by Gherardo Varando. Last updated 1 months ago.

8.0 match 8 stars 3.90 score 8 scripts

henryrscharf

anipaths:Animation of Multiple Trajectories with Uncertainty

Animation of observed trajectories using spline-based interpolation (see for example, Buderman, F. E., Hooten, M. B., Ivan, J. S. and Shenk, T. M. (2016), <doi:10.1111/2041-210X.12465> "A functional model for characterizing long-distance movement behaviour". Methods Ecol Evol). Intended to be used exploratory data analysis, and perhaps for preparation of presentations.

Maintained by Henry Scharf. Last updated 16 days ago.

10.6 match 2.92 score 14 scripts

r-simmer

simmer.bricks:Helper Methods for 'simmer' Trajectories

Provides wrappers for common activity patterns in 'simmer' trajectories.

Maintained by Iñaki Ucar. Last updated 2 years ago.

discrete-event simulation

5.4 match 6 stars 5.64 score 49 scripts 1 dependents

mightymetrika

OLStrajr:Ordinary Least Squares Trajectory Analysis

The 'OLStrajr' package provides comprehensive functions for ordinary least squares (OLS) trajectory analysis and case-by-case OLS regression as outlined in Carrig, Wirth, and Curran (2004) <doi:10.1207/S15328007SEM1101_9> and Rogosa and Saner (1995) <doi:10.3102/10769986020002149>. It encompasses two primary functions, OLStraj() and cbc_lm(). The OLStraj() function simplifies the estimation of individual growth curves over time via OLS regression, with options for visualizing both group-level and individual-level growth trajectories and support for linear and quadratic models. The cbc_lm() function facilitates case-by-case OLS estimates and provides unbiased mean population intercept and slope estimators by averaging OLS intercepts and slopes across cases. It further offers standard error calculations across bootstrap replicates and computation of 95% confidence intervals based on empirical distributions from the resampling processes.

Maintained by Mackson Ncube. Last updated 2 years ago.

7.7 match 4.00 score 6 scripts

pythonhealthdatascience

treat.sim:Nelson's Treatment Centre Simulation in Simmer

A discrete-event simulation of a simple urgent care treatment centre simulation from Nelson (2013). Implemented in R Simmer. The model is packaged to allow for easy experimentation, summary of results, and implementation in other software such as a Shiny interface.

Maintained by Thomas Monks. Last updated 8 months ago.

computer-simulation discrete-event-simulation health open-modelling open-science open-source r-language reproducible-research simmer

6.8 match 2 stars 4.48 score 5 scripts

yelleknek

MBESS:The MBESS R Package

Implements methods that are useful in designing research studies and analyzing data, with particular emphasis on methods that are developed for or used within the behavioral, educational, and social sciences (broadly defined). That being said, many of the methods implemented within MBESS are applicable to a wide variety of disciplines. MBESS has a suite of functions for a variety of related topics, such as effect sizes, confidence intervals for effect sizes (including standardized effect sizes and noncentral effect sizes), sample size planning (from the accuracy in parameter estimation [AIPE], power analytic, equivalence, and minimum-risk point estimation perspectives), mediation analysis, various properties of distributions, and a variety of utility functions. MBESS (pronounced 'em-bes') was originally an acronym for 'Methods for the Behavioral, Educational, and Social Sciences,' but MBESS became more general and now contains methods applicable and used in a wide variety of fields and is an orphan acronym, in the sense that what was an acronym is now literally its name. MBESS has greatly benefited from others, see <https://www3.nd.edu/~kkelley/site/MBESS.html> for a detailed list of those that have contributed and other details.

Maintained by Ken Kelley. Last updated 1 years ago.

3.7 match 2 stars 8.21 score 274 scripts 23 dependents

insightsengineering

rbmi:Reference Based Multiple Imputation

Implements standard and reference based multiple imputation methods for continuous longitudinal endpoints (Gower-Page et al. (2022) <doi:10.21105/joss.04251>). In particular, this package supports deterministic conditional mean imputation and jackknifing as described in Wolbers et al. (2022) <doi:10.1002/pst.2234>, Bayesian multiple imputation as described in Carpenter et al. (2013) <doi:10.1080/10543406.2013.834911>, and bootstrapped maximum likelihood imputation as described in von Hippel and Bartlett (2021) <doi: 10.1214/20-STS793>.

Maintained by Isaac Gravestock. Last updated 25 days ago.

3.4 match 18 stars 8.78 score 33 scripts 1 dependents

milanwiedemann

lcsm:Univariate and Bivariate Latent Change Score Modelling

Helper functions to implement univariate and bivariate latent change score models in R using the 'lavaan' package. For details about Latent Change Score Modeling (LCSM) see McArdle (2009) <doi:10.1146/annurev.psych.60.110707.163612> and Grimm, An, McArdle, Zonderman and Resnick (2012) <doi:10.1080/10705511.2012.659627>. The package automatically generates 'lavaan' syntax for different model specifications and varying timepoints. The 'lavaan' syntax generated by this package can be returned and further specifications can be added manually. Longitudinal plots as well as simplified path diagrams can be created to visualise data and model specifications. Estimated model parameters and fit statistics can be extracted as data frames. Data for different univariate and bivariate LCSM can be simulated by specifying estimates for model parameters to explore their effects. This package combines the strengths of other R packages like 'lavaan', 'broom', and 'semPlot' by generating 'lavaan' syntax that helps these packages work together.

Maintained by Milan Wiedemann. Last updated 2 years ago.

4.7 match 17 stars 6.34 score 43 scripts

constantino-garcia

nonlinearTseries:Nonlinear Time Series Analysis

Functions for nonlinear time series analysis. This package permits the computation of the most-used nonlinear statistics/algorithms including generalized correlation dimension, information dimension, largest Lyapunov exponent, sample entropy and Recurrence Quantification Analysis (RQA), among others. Basic routines for surrogate data testing are also included. Part of this work was based on the book "Nonlinear time series analysis" by Holger Kantz and Thomas Schreiber (ISBN: 9780521529020).

Maintained by Constantino A. Garcia. Last updated 6 months ago.

chaos chaotic-systems nonlinear-dynamics nonlinear-time-series time-series openblas cpp

3.3 match 35 stars 8.98 score 123 scripts 7 dependents

winvector

WVPlots:Common Plots for Analysis

Select data analysis plots, under a standardized calling interface implemented on top of 'ggplot2' and 'plotly'. Plots of interest include: 'ROC', gain curve, scatter plot with marginal distributions, conditioned scatter plot with marginal densities, box and stem with matching theoretical distribution, and density with matching theoretical distribution.

Maintained by John Mount. Last updated 11 months ago.

3.7 match 85 stars 8.00 score 280 scripts

bioc

RCSL:Rank Constrained Similarity Learning for single cell RNA sequencing data

A novel clustering algorithm and toolkit RCSL (Rank Constrained Similarity Learning) to accurately identify various cell types using scRNA-seq data from a complex tissue. RCSL considers both lo-cal similarity and global similarity among the cells to discern the subtle differences among cells of the same type as well as larger differences among cells of different types. RCSL uses Spearman’s rank correlations of a cell’s expression vector with those of other cells to measure its global similar-ity, and adaptively learns neighbour representation of a cell as its local similarity. The overall similar-ity of a cell to other cells is a linear combination of its global similarity and local similarity.

Maintained by Qinglin Mei. Last updated 5 months ago.

singlecell software clustering dimensionreduction rnaseq visualization sequencing

6.4 match 2 stars 4.48 score 10 scripts

mhahsler

pomdp:Infrastructure for Partially Observable Markov Decision Processes (POMDP)

Provides the infrastructure to define and analyze the solutions of Partially Observable Markov Decision Process (POMDP) models. Interfaces for various exact and approximate solution algorithms are available including value iteration, point-based value iteration and SARSOP. Smallwood and Sondik (1973) <doi:10.1287/opre.21.5.1071>.

Maintained by Michael Hahsler. Last updated 3 months ago.

control-theory markov-decision-processes optimization cpp

4.0 match 19 stars 7.03 score 21 scripts

functionaldata

fdapace:Functional Data Analysis and Empirical Dynamics

A versatile package that provides implementation of various methods of Functional Data Analysis (FDA) and Empirical Dynamics. The core of this package is Functional Principal Component Analysis (FPCA), a key technique for functional data analysis, for sparsely or densely sampled random trajectories and time courses, via the Principal Analysis by Conditional Estimation (PACE) algorithm. This core algorithm yields covariance and mean functions, eigenfunctions and principal component (scores), for both functional data and derivatives, for both dense (functional) and sparse (longitudinal) sampling designs. For sparse designs, it provides fitted continuous trajectories with confidence bands, even for subjects with very few longitudinal observations. PACE is a viable and flexible alternative to random effects modeling of longitudinal data. There is also a Matlab version (PACE) that contains some methods not available on fdapace and vice versa. Updates to fdapace were supported by grants from NIH Echo and NSF DMS-1712864 and DMS-2014626. Please cite our package if you use it (You may run the command citation("fdapace") to get the citation format and bibtex entry). References: Wang, J.L., Chiou, J., Müller, H.G. (2016) <doi:10.1146/annurev-statistics-041715-033624>; Chen, K., Zhang, X., Petersen, A., Müller, H.G. (2017) <doi:10.1007/s12561-015-9137-5>.

Maintained by Yidong Zhou. Last updated 9 months ago.

cpp

2.4 match 31 stars 11.46 score 474 scripts 25 dependents

mottastefano

SOMMD:Self Organising Maps for the Analysis of Molecular Dynamics Data

Processes data from Molecular Dynamics simulations using Self Organising Maps. Features include the ability to read different input formats. Trajectories can be analysed to identify groups of important frames. Output visualisation can be generated for maps and pathways. Methodological details can be found in Motta S et al (2022) <doi:10.1021/acs.jctc.1c01163>. I/O functions for xtc format files were implemented using the 'xdrfile' library available under open source license. The relevant information can be found in inst/COPYRIGHT.

Maintained by Stefano Motta. Last updated 6 months ago.

16.1 match 1.70 score 4 scripts

bioc

TrajectoryGeometry:This Package Discovers Directionality in Time and Pseudo-times Series of Gene Expression Patterns

Given a time series or pseudo-times series of gene expression data, we might wish to know: Do the changes in gene expression in these data exhibit directionality? Are there turning points in this directionality. Do different subsets of the data move in different directions? This package uses spherical geometry to probe these sorts of questions. In particular, if we are looking at (say) the first n dimensions of the PCA of gene expression, directionality can be detected as the clustering of points on the (n-1)-dimensional sphere.

Maintained by Michael Shapiro. Last updated 5 months ago.

biologicalquestion statisticalmethod geneexpression singlecell

5.9 match 4.60 score 7 scripts

rmi-pacta

pacta.loanbook:Easily Install and Load PACTA for Banks Packages

PACTA (Paris Agreement Capital Transition Assessment) for Banks is a tool that allows banks to calculate the climate alignment of their corporate lending portfolios. This package is designed to make it easy to install and load multiple PACTA for Banks packages in a single step. It also provides thorough documentation - the PACTA for Banks cookbook at <https://rmi-pacta.github.io/pacta.loanbook/articles/cookbook_overview.html> - on how to run a PACTA for Banks analysis. This covers prerequisites for the analysis, the separate steps of running the analysis, the interpretation of PACTA for Banks results, and advanced use cases.

Maintained by Jacob Kastl. Last updated 3 days ago.

5.8 match 1 stars 4.68 score 12 scripts

r-forge

R2MLwiN:Running 'MLwiN' from Within R

An R command interface to the 'MLwiN' multilevel modelling software package.

Maintained by Zhengzheng Zhang. Last updated 5 months ago.

4.9 match 5.35 score 125 scripts

joemsong

TreeDimensionTest:Trajectory Presence and Heterogeneity in Multivariate Data

Testing for trajectory presence and heterogeneity on multivariate data. Two statistical methods (Tenha & Song 2022) <doi:10.1371/journal.pcbi.1009829> are implemented. The tree dimension test quantifies the statistical evidence for trajectory presence. The subset specificity measure summarizes pattern heterogeneity using the minimum subtree cover. There is no user tunable parameters for either method. Examples are included to illustrate how to use the methods on single-cell data for studying gene and pathway expression dynamics and pathway expression specificity.

Maintained by Joe Song. Last updated 3 years ago.

cpp

9.5 match 2.70 score 1 scripts

lcbc-uio

galamm:Generalized Additive Latent and Mixed Models

Estimates generalized additive latent and mixed models using maximum marginal likelihood, as defined in Sorensen et al. (2023) <doi:10.1007/s11336-023-09910-z>, which is an extension of Rabe-Hesketh and Skrondal (2004)'s unifying framework for multilevel latent variable modeling <doi:10.1007/BF02295939>. Efficient computation is done using sparse matrix methods, Laplace approximation, and automatic differentiation. The framework includes generalized multilevel models with heteroscedastic residuals, mixed response types, factor loadings, smoothing splines, crossed random effects, and combinations thereof. Syntax for model formulation is close to 'lme4' (Bates et al. (2015) <doi:10.18637/jss.v067.i01>) and 'PLmixed' (Rockwood and Jeon (2019) <doi:10.1080/00273171.2018.1516541>).

Maintained by Øystein Sørensen. Last updated 6 months ago.

generalized-additive-models hierarchical-models item-response-theory latent-variable-models structural-equation-models cpp

3.4 match 29 stars 7.33 score 41 scripts

miguel-porto

SiMRiv:Simulating Multistate Movements in River/Heterogeneous Landscapes

Provides functions to generate and analyze spatially-explicit individual-based multistate movements in rivers, heterogeneous and homogeneous spaces. This is done by incorporating landscape bias on local behaviour, based on resistance rasters. Although originally conceived and designed to simulate trajectories of species constrained to linear habitats/dendritic ecological networks (e.g. river networks), the simulation algorithm is built to be highly flexible and can be applied to any (aquatic, semi-aquatic or terrestrial) organism, independently on the landscape in which it moves. Thus, the user will be able to use the package to simulate movements either in homogeneous landscapes, heterogeneous landscapes (e.g. semi-aquatic animal moving mainly along rivers but also using the matrix), or even in highly contrasted landscapes (e.g. fish in a river network). The algorithm and its input parameters are the same for all cases, so that results are comparable. Simulated trajectories can then be used as mechanistic null models (Potts & Lewis 2014, <DOI:10.1098/rspb.2014.0231>) to test a variety of 'Movement Ecology' hypotheses (Nathan et al. 2008, <DOI:10.1073/pnas.0800375105>), including landscape effects (e.g. resources, infrastructures) on animal movement and species site fidelity, or for predictive purposes (e.g. road mortality risk, dispersal/connectivity). The package should be relevant to explore a broad spectrum of ecological phenomena, such as those at the interface of animal behaviour, management, landscape and movement ecology, disease and invasive species spread, and population dynamics.

Maintained by Miguel Porto. Last updated 6 months ago.

animal-movement heterogeneous-landscapes movement-ecology river-networks simulation

4.1 match 15 stars 6.08 score 27 scripts 1 dependents

ropensci

spatsoc:Group Animal Relocation Data by Spatial and Temporal Relationship

Detects spatial and temporal groups in GPS relocations (Robitaille et al. (2019) <doi:10.1111/2041-210X.13215>). It can be used to convert GPS relocations to gambit-of-the-group format to build proximity-based social networks In addition, the randomizations function provides data-stream randomization methods suitable for GPS data.

Maintained by Alec L. Robitaille. Last updated 1 months ago.

animal gps network social spatial

2.5 match 24 stars 9.97 score 145 scripts 3 dependents

r-lidar

lidR:Airborne LiDAR Data Manipulation and Visualization for Forestry Applications

Airborne LiDAR (Light Detection and Ranging) interface for data manipulation and visualization. Read/write 'las' and 'laz' files, computation of metrics in area based approach, point filtering, artificial point reduction, classification from geographic data, normalization, individual tree segmentation and other manipulations.

Maintained by Jean-Romain Roussel. Last updated 1 months ago.

als forestry las laz lidar point-cloud remote-sensing openblas cpp openmp

1.7 match 623 stars 14.47 score 844 scripts 8 dependents

bioc

scHOT:single-cell higher order testing

Single cell Higher Order Testing (scHOT) is an R package that facilitates testing changes in higher order structure of gene expression along either a developmental trajectory or across space. scHOT is general and modular in nature, can be run in multiple data contexts such as along a continuous trajectory, between discrete groups, and over spatial orientations; as well as accommodate any higher order measurement such as variability or correlation. scHOT meaningfully adds to first order effect testing, such as differential expression, and provides a framework for interrogating higher order interactions from single cell data.

Maintained by Shila Ghazanfar. Last updated 5 months ago.

geneexpression rnaseq sequencing singlecell software transcriptomics

5.7 match 4.26 score 18 scripts

cran

kendallRandomWalks:Simulate and Visualize Kendall Random Walks and Related Distributions

Kendall random walks are a continuous-space Markov chains generated by the Kendall generalized convolution. This package provides tools for simulating these random walks and studying distributions related to them. For more information about Kendall random walks see Jasiulis-Gołdyn (2014) <arXiv:1412.0220>.

Maintained by Mateusz Staniak. Last updated 7 years ago.

7.4 match 3.26 score 18 scripts

bioc

LinkHD:LinkHD: a versatile framework to explore and integrate heterogeneous data

Here we present Link-HD, an approach to integrate heterogeneous datasets, as a generalization of STATIS-ACT (“Structuration des Tableaux A Trois Indices de la Statistique–Analyse Conjointe de Tableaux”), a family of methods to join and compare information from multiple subspaces. However, STATIS-ACT has some drawbacks since it only allows continuous data and it is unable to establish relationships between samples and features. In order to tackle these constraints, we incorporate multiple distance options and a linear regression based Biplot model in order to stablish relationships between observations and variable and perform variable selection.

Maintained by "Laura M Zingaretti". Last updated 5 months ago.

classification multiplecomparison regression software

6.0 match 4.00 score 2 scripts

tilburgnetworkgroup

remstats:Computes Statistics for Relational Event History Data

Computes a variety of statistics for relational event models. Relational event models enable researchers to investigate both exogenous and endogenous factors influencing the evolution of a time-ordered sequence of events. These models are categorized into tie-oriented models (Butts, C., 2008, <doi:10.1111/j.1467-9531.2008.00203.x>), where the probability of a dyad interacting next is modeled in a single step, and actor-oriented models (Stadtfeld, C., & Block, P., 2017, <doi:10.15195/v4.a14>), which first model the probability of a sender initiating an interaction and subsequently the probability of the sender's choice of receiver. The package is designed to compute a variety of statistics that summarize exogenous and endogenous influences on the event stream for both types of models.

Maintained by Giuseppe Arena. Last updated 2 months ago.

cpp

3.5 match 8 stars 6.72 score 44 scripts 1 dependents

bart1

moveWindSpeed:Estimate Wind Speeds from Bird Trajectories

Estimating wind speed from trajectories of individually tracked birds using a maximum likelihood approach from Weinzierl et al., 2016 <doi.org:10.1002/ece3.2585>.

Maintained by Bart Kranstauber. Last updated 2 years ago.

cpp

6.9 match 3.38 score 12 scripts

jeksterslab

cTMed:Continuous Time Mediation

Calculates standard errors and confidence intervals for effects in continuous-time mediation models. This package extends the work of Deboeck and Preacher (2015) <doi:10.1080/10705511.2014.973960> and Ryan and Hamaker (2021) <doi:10.1007/s11336-021-09767-0> by providing methods to generate standard errors and confidence intervals for the total, direct, and indirect effects in these models.

Maintained by Ivan Jacob Agaloos Pesigan. Last updated 21 days ago.

centrality continuous-time delta-method mediation monte-carlo-method network openblas cpp openmp

5.0 match 4.56 score 24 scripts

mhahsler

markovDP:Infrastructure for Discrete-Time Markov Decision Processes (MDP)

Provides the infrastructure to work with Markov Decision Processes (MDPs) in R. The focus is on convenience in formulating MDPs, the support of sparse representations (using sparse matrices, lists and data.frames) and visualization of results. Some key components are implemented in C++ to speed up computation. Several popular solvers are implemented.

Maintained by Michael Hahsler. Last updated 4 days ago.

control-theory markov-decision-process optimization cpp

4.0 match 7 stars 5.51 score 4 scripts

gobbios

EloRating:Animal Dominance Hierarchies by Elo Rating

Provides functions to quantify animal dominance hierarchies. The major focus is on Elo rating and its ability to deal with temporal dynamics in dominance interaction sequences. For static data, David's score and de Vries' I&SI are also implemented. In addition, the package provides functions to assess transitivity, linearity and stability of dominance networks. See Neumann et al (2011) <doi:10.1016/j.anbehav.2011.07.016> for an introduction.

Maintained by Christof Neumann. Last updated 8 months ago.

cpp

3.2 match 4 stars 6.86 score 61 scripts 1 dependents

tobiste

tectonicr:Analyzing the Orientation of Maximum Horizontal Stress

Models the direction of the maximum horizontal stress using relative plate motion parameters. Statistical algorithms to evaluate the modeling results compared with the observed data. Provides plots to visualize the results. Methods described in Stephan et al. (2023) <doi:10.1038/s41598-023-42433-2> and Wdowinski (1998) <doi:10.1016/S0079-1946(98)00091-3>.

Maintained by Tobias Stephan. Last updated 15 days ago.

geology structural-geology tectonics

3.0 match 7 stars 7.26 score 33 scripts

pik-piam

rmndt:Tools for data.table objects in the REMIND context

Helper functions for REMIND-related tasks with data.table objects, e.g., interpolation and (dis-)aggregation.

Maintained by Alois Dirnaichner. Last updated 11 months ago.

7.3 match 2.95 score 10 scripts 6 dependents

zheng206

ComBatFamQC:Comprehensive Batch Effect Diagnostics and Harmonization

Provides a comprehensive framework for batch effect diagnostics, harmonization, and post-harmonization downstream analysis. Features include interactive visualization tools, robust statistical tests, and a range of harmonization techniques. Additionally, 'ComBatFamQC' enables the creation of life-span age trend plots with estimated age-adjusted centiles and facilitates the generation of covariate-corrected residuals for analytical purposes. Methods for harmonization are based on approaches described in Johnson et al., (2007) <doi:10.1093/biostatistics/kxj037>, Beer et al., (2020) <doi:10.1016/j.neuroimage.2020.117129>, Pomponio et al., (2020) <doi:10.1016/j.neuroimage.2019.116450>, and Chen et al., (2021) <doi:10.1002/hbm.25688>.

Maintained by Zheng Ren. Last updated 19 hours ago.

diagnostic-tool harmonization rshinyapp

4.0 match 2 stars 5.41 score 16 scripts

anna-neufeld

splinetree:Longitudinal Regression Trees and Forests

Builds regression trees and random forests for longitudinal or functional data using a spline projection method. Implements and extends the work of Yu and Lambert (1999) <doi:10.1080/10618600.1999.10474847>. This method allows trees and forests to be built while considering either level and shape or only shape of response trajectories.

Maintained by Anna Neufeld. Last updated 6 years ago.

4.1 match 4 stars 5.24 score 29 scripts

bayesball

LearnBayes:Learning Bayesian Inference

Contains functions for summarizing basic one and two parameter posterior distributions and predictive distributions. It contains MCMC algorithms for summarizing posterior distributions defined by the user. It also contains functions for regression models, hierarchical models, Bayesian tests, and illustrations of Gibbs sampling.

Maintained by Jim Albert. Last updated 7 years ago.

1.9 match 38 stars 11.34 score 690 scripts 31 dependents

jmsigner

amt:Animal Movement Tools

Manage and analyze animal movement data. The functionality of 'amt' includes methods to calculate home ranges, track statistics (e.g. step lengths, speed, or turning angles), prepare data for fitting habitat selection analyses, and simulation of space-use from fitted step-selection functions.

Maintained by Johannes Signer. Last updated 4 months ago.

2.0 match 41 stars 10.54 score 418 scripts

euctrl-pru

HexAeroR:A package to determine used airports, runways, taxiways and stands based on available flight coordinates.

HexAeroR is a EUROCONTROL R package designed for aviation professionals and data analysts. It allows for the determination of used airports, runways, taxiways, and stands based on available (ADS-B) flight trajectory coordinates. This tool aims to enhance aviation data analysis, facilitating the extraction of milestones for performance analysis.

Maintained by Quinten Goens. Last updated 1 years ago.

adep ades aircraft airport apron detection eurocontrol h3 hexaero hexaeror runway stands taxiways trajectory uber

10.5 match 2.00 score 2 scripts

mc-schaaf

mousetRajectory:Mouse Trajectory Analyses for Behavioural Scientists

Helping psychologists and other behavioural scientists to analyze mouse movement (and other 2-D trajectory) data. Bundles together several functions that compute spatial measures (e.g., maximum absolute deviation, area under the curve, sample entropy) or provide a shorthand for procedures that are frequently used (e.g., time normalization, linear interpolation, extracting initiation and movement times). For more informationsee Pfister et al. (2024) <doi:10.20982/tqmp.20.3.p217>.

Maintained by Roland Pfister. Last updated 6 months ago.

5.2 match 2 stars 4.00 score 5 scripts

hputter

mstate:Data Preparation, Estimation and Prediction in Multi-State Models

Contains functions for data preparation, descriptives, hazard estimation and prediction with Aalen-Johansen or simulation in competing risks and multi-state models, see Putter, Fiocco, Geskus (2007) <doi:10.1002/sim.2712>.

Maintained by Hein Putter. Last updated 29 days ago.

1.7 match 11 stars 12.13 score 322 scripts 55 dependents

ropensci

slopes:Calculate Slopes of Roads, Rivers and Trajectories

Functions and example data to support research into the slope (also known as longitudinal gradient or steepness) of linear geographic entities such as roads <doi:10.1038/s41597-019-0147-x> and rivers <doi:10.1016/j.jhydrol.2018.06.066>. The package was initially developed to calculate the steepness of street segments but can be used to calculate steepness of any linear feature that can be represented as LINESTRING geometries in the 'sf' class system. The package takes two main types of input data for slope calculation: vector geographic objects representing linear features, and raster geographic objects with elevation values (which can be downloaded using functionality in the package) representing a continuous terrain surface. Where no raster object is provided the package attempts to download elevation data using the 'ceramic' package.

Maintained by Robin Lovelace. Last updated 5 months ago.

3.0 match 70 stars 6.91 score 39 scripts

agrdatasci

gdistance:Distances and Routes on Geographical Grids

Provides classes and functions to calculate various distance measures and routes in heterogeneous geographic spaces represented as grids. The package implements measures to model dispersal histories first presented by van Etten and Hijmans (2010) <doi:10.1371/journal.pone.0012060>. Least-cost distances as well as more complex distances based on (constrained) random walks can be calculated. The distances implemented in the package are used in geographical genetics, accessibility indicators, and may also have applications in other fields of geospatial analysis.

Maintained by Andrew Marx. Last updated 1 years ago.

2.0 match 17 stars 10.34 score 478 scripts 23 dependents

cecileproust-lima

lcmm:Extended Mixed Models Using Latent Classes and Latent Processes

Estimation of various extensions of the mixed models including latent class mixed models, joint latent class mixed models, mixed models for curvilinear outcomes, mixed models for multivariate longitudinal outcomes using a maximum likelihood estimation method (Proust-Lima, Philipps, Liquet (2017) <doi:10.18637/jss.v078.i02>).

Maintained by Cecile Proust-Lima. Last updated 1 months ago.

fortran

1.8 match 62 stars 11.41 score 249 scripts 7 dependents

manueleleonelli

bnRep:A Repository of Bayesian Networks from the Academic Literature

A collection of Bayesian networks (discrete, Gaussian, and conditional linear Gaussian) collated from recent academic literature. The 'bnRep_summary' object provides an overview of the Bayesian networks in the repository and the package documentation includes details about the variables in each network. A Shiny app to explore the repository can be launched with 'bnRep_app()' and is available online at <https://manueleleonelli.shinyapps.io/bnRep>. For details see <https://github.com/manueleleonelli/bnRep>.

Maintained by Manuele Leonelli. Last updated 6 months ago.

4.0 match 5 stars 5.10 score 7 scripts

bioc

iCheck:QC Pipeline and Data Analysis Tools for High-Dimensional Illumina mRNA Expression Data

QC pipeline and data analysis tools for high-dimensional Illumina mRNA expression data.

Maintained by Weiliang Qiu. Last updated 5 months ago.

geneexpression differentialexpression microarray preprocessing dnamethylation onechannel twochannel qualitycontrol

6.8 match 3.00 score 1 scripts

yeyuan98

clockSim:Simulation of the Circadian Clock Gene Network

A preconfigured simulation workflow for the circadian clock gene network.

Maintained by Ye Yuan. Last updated 8 days ago.

7.2 match 2.78 score 3 scripts

epiforecasts

EpiNow2:Estimate Real-Time Case Counts and Time-Varying Epidemiological Parameters

Estimates the time-varying reproduction number, rate of spread, and doubling time using a range of open-source tools (Abbott et al. (2020) <doi:10.12688/wellcomeopenres.16006.1>), and current best practices (Gostic et al. (2020) <doi:10.1101/2020.06.18.20134858>). It aims to help users avoid some of the limitations of naive implementations in a framework that is informed by community feedback and is actively supported.

Maintained by Sebastian Funk. Last updated 26 days ago.

backcalculation covid-19 gaussian-processes open-source reproduction-number stan cpp

1.7 match 120 stars 11.88 score 210 scripts

milanwiedemann

suddengains:Identify Sudden Gains in Longitudinal Data

Identify sudden gains based on the three criteria outlined by Tang and DeRubeis (1999) <doi:10.1037/0022-006X.67.6.894> to a selection of repeated measures. Sudden losses, defined as the opposite of sudden gains can also be identified. Two different datasets can be created, one including all sudden gains/losses and one including one selected sudden gain/loss for each case. It can extract scores around sudden gains/losses. It can plot the average change around sudden gains/losses and trajectories of individual cases.

Maintained by Milan Wiedemann. Last updated 2 years ago.

change-detection sudden-gains sudden-losses

3.8 match 7 stars 5.15 score 10 scripts

bioboot

bio3d:Biological Structure Analysis

Utilities to process, organize and explore protein structure, sequence and dynamics data. Features include the ability to read and write structure, sequence and dynamic trajectory data, perform sequence and structure database searches, data summaries, atom selection, alignment, superposition, rigid core identification, clustering, torsion analysis, distance matrix analysis, structure and sequence conservation analysis, normal mode analysis, principal component analysis of heterogeneous structure data, and correlation network analysis from normal mode and molecular dynamics data. In addition, various utility functions are provided to enable the statistical and graphical power of the R environment to work with biological sequence and structural data. Please refer to the URLs below for more information.

Maintained by Barry Grant. Last updated 5 months ago.

zlib cpp

2.3 match 5 stars 8.49 score 1.4k scripts 10 dependents

pik-piam

mrindustry:input data generation for the REMIND industry module

The mrindustry packages contains data preprocessing for the REMIND model.

Maintained by Falk Benke. Last updated 10 hours ago.

3.6 match 5.43 score 2 dependents

archidart

archiDART:Plant Root System Architecture Analysis Using DART and RSML Files

Analysis of complex plant root system architectures (RSA) using the output files created by Data Analysis of Root Tracings (DART), an open-access software dedicated to the study of plant root architecture and development across time series (Le Bot et al (2010) "DART: a software to analyse root system architecture and development from captured images", Plant and Soil, <DOI:10.1007/s11104-009-0005-2>), and RSA data encoded with the Root System Markup Language (RSML) (Lobet et al (2015) "Root System Markup Language: toward a unified root architecture description language", Plant Physiology, <DOI:10.1104/pp.114.253625>). More information can be found in Delory et al (2016) "archiDART: an R package for the automated computation of plant root architectural traits", Plant and Soil, <DOI:10.1007/s11104-015-2673-4>.

Maintained by Benjamin M Delory. Last updated 4 years ago.

4.8 match 2 stars 4.02 score 13 scripts

uzh-peg

microxanox:Oxic-Anoxic Regime Shifts in Microbial Communities

Model to simulate a three functional group system with four chemical substrates using a set of ordinary differential equations. Simulations can be run individually or over a parameter range, to find stable states. The model features multiple species per functional group, where the number is only limited by computational constraints. The R package is constructed in such a way, that the results contain the input parameter used, so that a saved results can be loaded again and thesimulation be repeated.

Maintained by Owen L. Petchey. Last updated 1 years ago.

4.9 match 3.85 score 35 scripts

j-hai

Synth:Synthetic Control Group Method for Comparative Case Studies

Implements the synthetic control group method for comparative case studies as described in Abadie and Gardeazabal (2003) and Abadie, Diamond, and Hainmueller (2010, 2011, 2014). The synthetic control method allows for effect estimation in settings where a single unit (a state, country, firm, etc.) is exposed to an event or intervention. It provides a data-driven procedure to construct synthetic control units based on a weighted combination of comparison units that approximates the characteristics of the unit that is exposed to the intervention. A combination of comparison units often provides a better comparison for the unit exposed to the intervention than any comparison unit alone.

Maintained by Jens Hainmueller. Last updated 2 years ago.

3.4 match 12 stars 5.50 score 444 scripts 1 dependents

alessandromagrini

gbmt:Group-Based Multivariate Trajectory Modeling

Estimation and analysis of group-based multivariate trajectory models (Nagin, 2018 <doi:10.1177/0962280216673085>; Magrini, 2022 <doi:10.1007/s10182-022-00437-9>). The package implements an Expectation-Maximization (EM) algorithm allowing unbalanced panel and missing values, and provides several functionalities for prediction and graphical representation.

Maintained by Alessandro Magrini. Last updated 4 months ago.

12.2 match 3 stars 1.52 score 11 scripts

openpharma

crmPack:Object-Oriented Implementation of CRM Designs

Implements a wide range of model-based dose escalation designs, ranging from classical and modern continual reassessment methods (CRMs) based on dose-limiting toxicity endpoints to dual-endpoint designs taking into account a biomarker/efficacy outcome. The focus is on Bayesian inference, making it very easy to setup a new design with its own JAGS code. However, it is also possible to implement 3+3 designs for comparison or models with non-Bayesian estimation. The whole package is written in a modular form in the S4 class system, making it very flexible for adaptation to new models, escalation or stopping rules. Further details are presented in Sabanes Bove et al. (2019) <doi:10.18637/jss.v089.i10>.

Maintained by Daniel Sabanes Bove. Last updated 2 months ago.

jags cpp

2.4 match 21 stars 7.79 score 208 scripts

cran

roots:Reconstructing Ordered Ontogenic Trajectories

A set of tools to reconstruct ordered ontogenic trajectories from single cell RNAseq data.

Maintained by Wajid Jawaid. Last updated 8 years ago.

6.8 match 2.70 score

inventionate

TimeSpaceAnalysis:Statistical tools for time-space analysis

Use Geometric Data Analysis approaches (e.g. MCA or MFA), time pattern analysis (see "time sequence clustering") and places chronologies (see "time geography") analysis.

Maintained by Fabian Mundt. Last updated 8 days ago.

7.4 match 2.48 score 2 scripts

billpetti

baseballr:Acquiring and Analyzing Baseball Data

Provides numerous utilities for acquiring and analyzing baseball data from online sources such as 'Baseball Reference' <https://www.baseball-reference.com/>, 'FanGraphs' <https://www.fangraphs.com/>, and the 'MLB Stats' API <https://www.mlb.com/>.

Maintained by Saiem Gilani. Last updated 4 months ago.

baseball pitchfx sabermetrics statcast

2.0 match 380 stars 8.98 score 582 scripts

bioc

mist:Differential Methylation Analysis for scDNAm Data

mist (Methylation Inference for Single-cell along Trajectory) is a hierarchical Bayesian framework for modeling DNA methylation trajectories and performing differential methylation (DM) analysis in single-cell DNA methylation (scDNAm) data. It estimates developmental-stage-specific variations, identifies genomic features with drastic changes along pseudotime, and, for two phenotypic groups, detects features with distinct temporal methylation patterns. mist uses Gibbs sampling to estimate parameters for temporal changes and stage-specific variations.

Maintained by Daoyu Duan. Last updated 2 months ago.

epigenetics differentialmethylation dnamethylation singlecell software

3.6 match 4.73 score 12 scripts

craig-pt

tsgc:Time Series Methods Based on Growth Curves

The 'tsgc' package provides comprehensive tools for the analysis and forecasting of epidemic trajectories. It is designed to model the progression of an epidemic over time while accounting for the various uncertainties inherent in real-time data. Underpinned by a dynamic Gompertz model, the package adopts a state space approach, using the Kalman filter for flexible and robust estimation of the non-linear growth pattern commonly observed in epidemic data. The reinitialization feature enhances the model’s ability to adapt to the emergence of new waves. The forecasts generated by the package are of value to public health officials and researchers who need to understand and predict the course of an epidemic to inform decision-making. Beyond its application in public health, the package is also a useful resource for researchers and practitioners in fields where the trajectories of interest resemble those of epidemics, such as innovation diffusion. The package includes functionalities for data preprocessing, model fitting, and forecast visualization, as well as tools for evaluating forecast accuracy. The core methodologies implemented in 'tsgc' are based on well-established statistical techniques as described in Harvey and Kattuman (2020) <doi:10.1162/99608f92.828f40de>, Harvey and Kattuman (2021) <doi:10.1098/rsif.2021.0179>, and Ashby, Harvey, Kattuman, and Thamotheram (2024) <https://www.jbs.cam.ac.uk/wp-content/uploads/2024/03/cchle-tsgc-paper-2024.pdf>.

Maintained by Craig Thamotheram. Last updated 7 months ago.

3.5 match 1 stars 4.86 score 24 scripts

bioc

singleCellTK:Comprehensive and Interactive Analysis of Single Cell RNA-Seq Data

The Single Cell Toolkit (SCTK) in the singleCellTK package provides an interface to popular tools for importing, quality control, analysis, and visualization of single cell RNA-seq data. SCTK allows users to seamlessly integrate tools from various packages at different stages of the analysis workflow. A general "a la carte" workflow gives users the ability access to multiple methods for data importing, calculation of general QC metrics, doublet detection, ambient RNA estimation and removal, filtering, normalization, batch correction or integration, dimensionality reduction, 2-D embedding, clustering, marker detection, differential expression, cell type labeling, pathway analysis, and data exporting. Curated workflows can be used to run Seurat and Celda. Streamlined quality control can be performed on the command line using the SCTK-QC pipeline. Users can analyze their data using commands in the R console or by using an interactive Shiny Graphical User Interface (GUI). Specific analyses or entire workflows can be summarized and shared with comprehensive HTML reports generated by Rmarkdown. Additional documentation and vignettes can be found at camplab.net/sctk.

Maintained by Joshua David Campbell. Last updated 25 days ago.

singlecell geneexpression differentialexpression alignment clustering immunooncology batcheffect normalization qualitycontrol dataimport gui

1.7 match 181 stars 10.16 score 252 scripts

hanase

bayesMig:Bayesian Projection of Migration

Producing probabilistic projections of net migration rate for all countries of the world or for subnational units using a Bayesian hierarchical model by Azose an Raftery (2015) <doi:10.1007/s13524-015-0415-0>.

Maintained by Hana Sevcikova. Last updated 4 months ago.

17.1 match 1.00 score 3 scripts

dgrun

RaceID:Identification of Cell Types, Inference of Lineage Trees, and Prediction of Noise Dynamics from Single-Cell RNA-Seq Data

Application of 'RaceID' allows inference of cell types and prediction of lineage trees by the 'StemID2' algorithm (Herman, J.S., Sagar, Grun D. (2018) <DOI:10.1038/nmeth.4662>). 'VarID2' is part of this package and allows quantification of biological gene expression noise at single-cell resolution (Rosales-Alvarez, R.E., Rettkowski, J., Herman, J.S., Dumbovic, G., Cabezas-Wallscheid, N., Grun, D. (2023) <DOI:10.1186/s13059-023-02974-1>).

Maintained by Dominic Grün. Last updated 4 months ago.

cpp

3.6 match 4.74 score 110 scripts

erhard-lab

HetSeq:Identifying Modulators of Cellular Responses Leveraging Intercellular Heterogeneity

Cellular responses to perturbations are highly heterogeneous and depend largely on the initial state of cells. Connecting post-perturbation cells via cellular trajectories to untreated cells (e.g. by leveraging metabolic labeling information) enables exploitation of intercellular heterogeneity as a combined knock-down and overexpression screen to identify pathway modulators, termed Heterogeneity-seq (see 'Berg et al' <doi:10.1101/2024.10.28.620481>). This package contains functions to generate cellular trajectories based on scSLAM-seq (single-cell, thiol-(SH)-linked alkylation of RNA for metabolic labelling sequencing) time courses, functions to identify pathway modulators and to visualize the results.

Maintained by Kevin Berg. Last updated 1 months ago.

4.8 match 3.54 score

gdurif

funStatTest:Statistical Testing for Functional Data

Implementation of two sample comparison procedures based on median-based statistical tests for functional data, introduced in Smida et al (2022) <doi:10.1080/10485252.2022.2064997>. Other competitive state-of-the-art approaches proposed by Chakraborty and Chaudhuri (2015) <doi:10.1093/biomet/asu072>, Horvath et al (2013) <doi:10.1111/j.1467-9868.2012.01032.x> or Cuevas et al (2004) <doi:10.1016/j.csda.2003.10.021> are also included in the package, as well as procedures to run test result comparisons and power analysis using simulations.

Maintained by Ghislain Durif. Last updated 10 months ago.

6.2 match 2.70 score 4 scripts

venelin

POUMM:The Phylogenetic Ornstein-Uhlenbeck Mixed Model

The Phylogenetic Ornstein-Uhlenbeck Mixed Model (POUMM) allows to estimate the phylogenetic heritability of continuous traits, to test hypotheses of neutral evolution versus stabilizing selection, to quantify the strength of stabilizing selection, to estimate measurement error and to make predictions about the evolution of a phenotype and phenotypic variation in a population. The package implements combined maximum likelihood and Bayesian inference of the univariate Phylogenetic Ornstein-Uhlenbeck Mixed Model, fast parallel likelihood calculation, maximum likelihood inference of the genotypic values at the tips, functions for summarizing and plotting traces and posterior samples, functions for simulation of a univariate continuous trait evolution model along a phylogenetic tree. So far, the package has been used for estimating the heritability of quantitative traits in macroevolutionary and epidemiological studies, see e.g. Bertels et al. (2017) <doi:10.1093/molbev/msx246> and Mitov and Stadler (2018) <doi:10.1093/molbev/msx328>. The algorithm for parallel POUMM likelihood calculation has been published in Mitov and Stadler (2019) <doi:10.1111/2041-210X.13136>.

Maintained by Venelin Mitov. Last updated 4 years ago.

cpp

3.3 match 4 stars 4.94 score 22 scripts

cran

icmstate:Interval Censored Multi-State Models

Allows for the non-parametric estimation of transition intensities in interval-censored multi-state models using the approach of Gomon and Putter (2024) <doi:10.48550/arXiv.2409.07176> or Gu et al. (2023) <doi:10.1093/biomet/asad073>.

Maintained by Daniel Gomon. Last updated 4 months ago.

cpp

4.5 match 3.65 score 15 scripts

bbsbayes

bbsBayes2:Hierarchical Bayesian Analysis of North American BBS Data

The North American Breeding Bird Survey (BBS) is a long-running program that seeks to monitor the status and trends of the breeding birds in North America. Since its start in 1966, the BBS has accumulated over 50 years of data for over 500 species of North American Birds. Given the temporal and spatial structure of the data, hierarchical Bayesian models are used to assess the status and trends of these 500+ species of birds. 'bbsBayes2' allows you to perform hierarchical Bayesian analysis of BBS data. You can run a full model analysis for one or more species that you choose, or you can take more control and specify how the data should be stratified, prepared for 'Stan', or modelled.

Maintained by Brandon P.M. Edwards. Last updated 2 months ago.

3.5 match 8 stars 4.64 score 121 scripts

smac-group

gmwmx2:Estimate Functional and Stochastic Parameters of Linear Models with Correlated Residuals and Missing Data

Implements the Generalized Method of Wavelet Moments with Exogenous Inputs estimator (GMWMX) presented in Voirol, L., Xu, H., Zhang, Y., Insolia, L., Molinari, R. and Guerrier, S. (2024) <doi:10.48550/arXiv.2409.05160>. The GMWMX estimator allows to estimate functional and stochastic parameters of linear models with correlated residuals in presence of missing data. The 'gmwmx2' package provides functions to load and plot Global Navigation Satellite System (GNSS) data from the Nevada Geodetic Laboratory and functions to estimate linear model model with correlated residuals in presence of missing data.

Maintained by Lionel Voirol. Last updated 3 days ago.

openblas cpp

3.1 match 2 stars 5.30 score

bioc

BioTIP:BioTIP: An R package for characterization of Biological Tipping-Point

Adopting tipping-point theory to transcriptome profiles to unravel disease regulatory trajectory.

Maintained by Yuxi (Jennifer) Sun. Last updated 5 months ago.

sequencing rnaseq geneexpression transcription software

2.3 match 18 stars 6.84 score 37 scripts

cjvanlissa

tidySEM:Tidy Structural Equation Modeling

A tidy workflow for generating, estimating, reporting, and plotting structural equation models using 'lavaan', 'OpenMx', or 'Mplus'. Throughout this workflow, elements of syntax, results, and graphs are represented as 'tidy' data, making them easy to customize. Includes functionality to estimate latent class analyses, and to plot 'dagitty' and 'igraph' objects.

Maintained by Caspar J. van Lissa. Last updated 8 days ago.

1.5 match 58 stars 10.69 score 330 scripts 1 dependents

biodiverse

ubms:Bayesian Models for Data from Unmarked Animals using 'Stan'

Fit Bayesian hierarchical models of animal abundance and occurrence via the 'rstan' package, the R interface to the 'Stan' C++ library. Supported models include single-season occupancy, dynamic occupancy, and N-mixture abundance models. Covariates on model parameters are specified using a formula-based interface similar to package 'unmarked', while also allowing for estimation of random slope and intercept terms. References: Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>; Fiske and Chandler (2011) <doi:10.18637/jss.v043.i10>.

Maintained by Ken Kellner. Last updated 19 days ago.

distance-sampling hierarchical-models n-mixture-model occupancy stan openblas cpp

2.0 match 35 stars 7.88 score 73 scripts

hms-dbmi

EHRtemporalVariability:Delineating Temporal Dataset Shifts in Electronic Health Records

Functions to delineate temporal dataset shifts in Electronic Health Records through the projection and visualization of dissimilarities among data temporal batches. This is done through the estimation of data statistical distributions over time and their projection in non-parametric statistical manifolds, uncovering the patterns of the data latent temporal variability. 'EHRtemporalVariability' is particularly suitable for multi-modal data and categorical variables with a high number of values, common features of biomedical data where traditional statistical process control or time-series methods may not be appropriate. 'EHRtemporalVariability' allows you to explore and identify dataset shifts through visual analytics formats such as Data Temporal heatmaps and Information Geometric Temporal (IGT) plots. An additional 'EHRtemporalVariability' Shiny app can be used to load and explore the package results and even to allow the use of these functions to those users non-experienced in R coding. (Sáez et al. 2020) <doi:10.1093/gigascience/giaa079>.

Maintained by Carlos Sáez. Last updated 11 months ago.

biomedical-data-science biomedical-informatics data-quality data-quality-monitoring dataset-shifts electronic-health-records time variability visualization

3.0 match 17 stars 5.27 score 22 scripts

bayesball

ProbBayes:Probability and Bayesian Modeling

Functions and datasets to accompany J. Albert and J. Hu, "Probability and Bayesian Modeling", CRC Press, (2019, ISBN: 1138492566).

Maintained by Jim Albert. Last updated 4 years ago.

3.6 match 5 stars 4.30 score 80 scripts

matthias-studer

WeightedCluster:Clustering of Weighted Data

Clusters state sequences and weighted data. It provides an optimized weighted PAM algorithm as well as functions for aggregating replicated cases, computing cluster quality measures for a range of clustering solutions and plotting (fuzzy) clusters of state sequences. Parametric bootstraps methods to validate typology of sequences are also provided. Finally, it provides a fuzzy and crisp CLARA algorithm to cluster large database with sequence analysis.

Maintained by Matthias Studer. Last updated 3 months ago.

cpp

2.7 match 5.55 score 106 scripts 4 dependents

mlysy

msde:Bayesian Inference for Multivariate Stochastic Differential Equations

Implements an MCMC sampler for the posterior distribution of arbitrary time-homogeneous multivariate stochastic differential equation (SDE) models with possibly latent components. The package provides a simple entry point to integrate user-defined models directly with the sampler's C++ code, and parallelizes large portions of the calculations when compiled with 'OpenMP'.

Maintained by Martin Lysy. Last updated 3 years ago.

cpp

3.1 match 4.91 score 27 scripts

dkaschek

dMod:Dynamic Modeling and Parameter Estimation in ODE Models

The framework provides functions to generate ODEs of reaction networks, parameter transformations, observation functions, residual functions, etc. The framework follows the paradigm that derivative information should be used for optimization whenever possible. Therefore, all major functions produce and can handle expressions for symbolic derivatives.

Maintained by Daniel Kaschek. Last updated 11 days ago.

1.8 match 20 stars 8.35 score 251 scripts

bioc

cicero:Predict cis-co-accessibility from single-cell chromatin accessibility data

Cicero computes putative cis-regulatory maps from single-cell chromatin accessibility data. It also extends monocle 2 for use in chromatin accessibility data.

Maintained by Hannah Pliner. Last updated 5 months ago.

sequencing clustering cellbasedassays immunooncology generegulation genetarget epigenetics atacseq singlecell

2.5 match 5.80 score 312 scripts

olivierpds

MplusLGM:Automate Latent Growth Mixture Modelling in 'Mplus'

Provide a suite of functions for conducting and automating Latent Growth Modeling (LGM) in 'Mplus', including Growth Curve Model (GCM), Growth-Based Trajectory Model (GBTM) and Latent Class Growth Analysis (LCGA). The package builds upon the capabilities of the 'MplusAutomation' package (Hallquist & Wiley, 2018) to streamline large-scale latent variable analyses. “MplusAutomation: An R Package for Facilitating Large-Scale Latent Variable Analyses in Mplus.” Structural Equation Modeling, 25(4), 621–638. <doi:10.1080/10705511.2017.1402334> The workflow implemented in this package follows the recommendations outlined in Van Der Nest et al. (2020). “An Overview of Mixture Modeling for Latent Evolutions in Longitudinal Data: Modeling Approaches, Fit Statistics, and Software.” Advances in Life Course Research, 43, Article 100323. <doi:10.1016/j.alcr.2019.100323>.

Maintained by Olivier Percie du Sert. Last updated 1 months ago.

mplus mplusautomation

3.9 match 4 stars 3.60 score

cran

XDNUTS:Discontinuous Hamiltonian Monte Carlo with Varying Trajectory Length

Hamiltonian Monte Carlo for both continuous and discontinuous posterior distributions with customisable trajectory length termination criterion. See Nishimura et al. (2020) <doi:10.1093/biomet/asz083> for the original Discontinuous Hamiltonian Monte Carlo, Hoffman et al. (2014) <doi:10.48550/arXiv.1111.4246> and Betancourt (2016) <doi:10.48550/arXiv.1601.00225> for the definition of possible Hamiltonian Monte Carlo termination criteria.

Maintained by Paolo Manildo. Last updated 2 months ago.

openblas cpp openmp

5.1 match 2.78 score

emerykevin

seqimpute:Imputation of Missing Data in Sequence Analysis

Multiple imputation of missing data in a dataset using MICT or MICT-timing methods. The core idea of the algorithms is to fill gaps of missing data, which is the typical form of missing data in a longitudinal setting, recursively from their edges. Prediction is based on either a multinomial or random forest regression model. Covariates and time-dependent covariates can be included in the model.

Maintained by Kevin Emery. Last updated 2 months ago.

3.5 match 3.78 score 1 scripts

pabrod

kinematics:Studying Sampled Trajectories

Allows analyzing time series representing two-dimensional movements. It accepts a data frame with a time (t), horizontal (x) and vertical (y) coordinate as columns, and returns several dynamical properties such as speed, acceleration or curvature.

Maintained by Pablo Rodriguez-Sanchez. Last updated 8 months ago.

biology ethology kinematics

3.3 match 1 stars 4.00 score 9 scripts

codymarquart

rENA:Epistemic Network Analysis

ENA (Shaffer, D. W. (2017) Quantitative Ethnography. ISBN: 0578191687) is a method used to identify meaningful and quantifiable patterns in discourse or reasoning. ENA moves beyond the traditional frequency-based assessments by examining the structure of the co-occurrence, or connections in coded data. Moreover, compared to other methodological approaches, ENA has the novelty of (1) modeling whole networks of connections and (2) affording both quantitative and qualitative comparisons between different network models. Shaffer, D.W., Collier, W., & Ruis, A.R. (2016).

Maintained by Cody L Marquart. Last updated 1 years ago.

openblas cpp

5.9 match 1 stars 2.26 score 36 scripts

venelin

PCMBase:Simulation and Likelihood Calculation of Phylogenetic Comparative Models

Phylogenetic comparative methods represent models of continuous trait data associated with the tips of a phylogenetic tree. Examples of such models are Gaussian continuous time branching stochastic processes such as Brownian motion (BM) and Ornstein-Uhlenbeck (OU) processes, which regard the data at the tips of the tree as an observed (final) state of a Markov process starting from an initial state at the root and evolving along the branches of the tree. The PCMBase R package provides a general framework for manipulating such models. This framework consists of an application programming interface for specifying data and model parameters, and efficient algorithms for simulating trait evolution under a model and calculating the likelihood of model parameters for an assumed model and trait data. The package implements a growing collection of models, which currently includes BM, OU, BM/OU with jumps, two-speed OU as well as mixed Gaussian models, in which different types of the above models can be associated with different branches of the tree. The PCMBase package is limited to trait-simulation and likelihood calculation of (mixed) Gaussian phylogenetic models. The PCMFit package provides functionality for inference of these models to tree and trait data. The package web-site <https://venelin.github.io/PCMBase/> provides access to the documentation and other resources.

Maintained by Venelin Mitov. Last updated 10 months ago.

1.8 match 6 stars 7.56 score 85 scripts 3 dependents

blue-matter

MSEtool:Management Strategy Evaluation Toolkit

Development, simulation testing, and implementation of management procedures for fisheries (see Carruthers & Hordyk (2018) <doi:10.1111/2041-210X.13081>).

Maintained by Adrian Hordyk. Last updated 27 days ago.

cpp

1.7 match 8 stars 7.69 score 163 scripts 3 dependents

bioc

veloviz:VeloViz: RNA-velocity informed 2D embeddings for visualizing cell state trajectories

VeloViz uses each cell’s current observed and predicted future transcriptional states inferred from RNA velocity analysis to build a nearest neighbor graph between cells in the population. Edges are then pruned based on a cosine correlation threshold and/or a distance threshold and the resulting graph is visualized using a force-directed graph layout algorithm. VeloViz can help ensure that relationships between cell states are reflected in the 2D embedding, allowing for more reliable representation of underlying cellular trajectories.

Maintained by Lyla Atta. Last updated 5 months ago.

transcriptomics visualization geneexpression sequencing rnaseq dimensionreduction cpp

3.3 match 4.00 score 6 scripts

fbertran

SelectBoost:A General Algorithm to Enhance the Performance of Variable Selection Methods in Correlated Datasets

An implementation of the selectboost algorithm (Bertrand et al. 2020, 'Bioinformatics', <doi:10.1093/bioinformatics/btaa855>), which is a general algorithm that improves the precision of any existing variable selection method. This algorithm is based on highly intensive simulations and takes into account the correlation structure of the data. It can either produce a confidence index for variable selection or it can be used in an experimental design planning perspective.

Maintained by Frederic Bertrand. Last updated 2 years ago.

confidence correlation correlation-structure modelling precision recall selection-algorithm

2.3 match 7 stars 5.61 score 13 scripts 1 dependents

rmendels

rerddapXtracto:Extracts Environmental Data from 'ERDDAP™' Web Services

Contains three functions that access environmental data from any 'ERDDAP™' data web service. The rxtracto() function extracts data along a trajectory for a given "radius" around the point. The rxtracto_3D() function extracts data in a box. The rxtractogon() function extracts data in a polygon. All of those three function use the 'rerddap' package to extract the data, and should work with any 'ERDDAP™' server. There are also two functions, plotBBox() and plotTrack() that use the 'plotdap' package to simplify the creation of maps of the data.

Maintained by Roy Mendelssohn. Last updated 19 days ago.

2.2 match 14 stars 5.79 score 44 scripts

statnet

ergmgp:Tools for Modeling ERGM Generating Processes

Provides tools for simulating draws from continuous time processes with well-defined exponential family random graph (ERGM) equilibria, i.e. ERGM generating processes (EGPs). A number of EGPs are supported, including the families identified in Butts (2023) <doi:10.1080/0022250X.2023.2180001>, as are functions for hazard calculation and timing calibration.

Maintained by Carter T. Butts. Last updated 5 months ago.

3.5 match 8 stars 3.60 score 1 scripts

jedalong

wildlifeDI:Calculate Indices of Dynamic Interaction for Wildlife Tracking Data

Dynamic interaction refers to spatial-temporal associations in the movements of two (or more) animals. This package provides tools for calculating a suite of indices used for quantifying dynamic interaction with wildlife telemetry data. For more information on each of the methods employed see the references within. The package (as of version >= 0.3) also has new tools for automating contact analysis in large tracking datasets. The package (as of version 1.0) uses the 'move2' class of objects for working with tracking dataset.

Maintained by Jed Long. Last updated 10 months ago.

1.9 match 16 stars 6.70 score 31 scripts

argocanada

argoFloats:Analysis of Oceanographic Argo Floats

Supports the analysis of oceanographic data recorded by Argo autonomous drifting profiling floats. Functions are provided to (a) download and cache data files, (b) subset data in various ways, (c) handle quality-control flags and (d) plot the results according to oceanographic conventions. A shiny app is provided for easy exploration of datasets. The package is designed to work well with the 'oce' package, providing a wide range of processing capabilities that are particular to oceanographic analysis. See Kelley, Harbin, and Richards (2021) <doi:10.3389/fmars.2021.635922> for more on the scientific context and applications.

Maintained by Dan Kelley. Last updated 1 months ago.

1.7 match 17 stars 7.32 score 203 scripts

mrc-ide

dust2:Next Generation dust

Experimental sources for the next generation of dust, which will properly adopt the particle filter, have support for partial parameter updates, support for multiple parameter sets and hopefully better GPU/MPI support.

Maintained by Rich FitzJohn. Last updated 11 days ago.

cpp openmp

1.9 match 6.66 score 32 scripts 2 dependents

bioc

traviz:Trajectory functions for visualization and interpretation.

traviz provides a suite of functions to plot trajectory related objects from Bioconductor packages. It allows plotting trajectories in reduced dimension, as well as averge gene expression smoothers as a function of pseudotime. Asides from general utility functions, traviz also allows plotting trajectories estimated by Slingshot, as well as smoothers estimated by tradeSeq. Furthermore, it allows for visualization of Slingshot trajectories using ggplot2.

Maintained by Koen Van den Berge. Last updated 5 months ago.

geneexpression rnaseq sequencing software singlecell transcriptomics visualization

4.1 match 3.00 score 2 scripts

floo66

cylcop:Circular-Linear Copulas with Angular Symmetry for Movement Data

Classes (S4) of circular-linear, symmetric copulas with corresponding methods, extending the 'copula' package. These copulas are especially useful for modeling correlation in discrete-time movement data. Methods for density, (conditional) distribution, random number generation, bivariate dependence measures and fitting parameters using maximum likelihood and other approaches. The package also contains methods for visualizing movement data and copulas.

Maintained by Florian Hodel. Last updated 2 years ago.

7.3 match 1 stars 1.70 score

bucky2177

dRiftDM:Estimating (Time-Dependent) Drift Diffusion Models

Fit and explore Drift Diffusion Models (DDMs), a common tool in psychology for describing decision processes in simple tasks. It can handle both time-independent and time-dependent DDMs. You either choose prebuilt models or create your own, and the package takes care of model predictions and parameter estimation. Model predictions are derived via the numerical solutions provided by Richter, Ulrich, and Janczyk (2023, <doi:10.1016/j.jmp.2023.102756>).

Maintained by Valentin Koob. Last updated 13 days ago.

cpp

1.9 match 6 stars 6.58 score 5 scripts

geobosh

sarima:Simulation and Prediction with Seasonal ARIMA Models

Functions, classes and methods for time series modelling with ARIMA and related models. The aim of the package is to provide consistent interface for the user. For example, a single function autocorrelations() computes various kinds of theoretical and sample autocorrelations. This is work in progress, see the documentation and vignettes for the current functionality. Function sarima() fits extended multiplicative seasonal ARIMA models with trends, exogenous variables and arbitrary roots on the unit circle, which can be fixed or estimated (for the algebraic basis for this see <arXiv:2208.05055>, a paper on the methodology is being prepared).

Maintained by Georgi N. Boshnakov. Last updated 12 months ago.

arima kalman-filter reg-sarima sarima sarimax seasonal time-series xarima openblas cpp

1.8 match 3 stars 6.71 score 112 scripts 1 dependents

jgarriga65

EMbC:Expectation-Maximization Binary Clustering

Unsupervised, multivariate, binary clustering for meaningful annotation of data, taking into account the uncertainty in the data. A specific constructor for trajectory analysis in movement ecology yields behavioural annotation of trajectories based on estimated local measures of velocity and turning angle, eventually with solar position covariate as a daytime indicator, ("Expectation-Maximization Binary Clustering for Behavioural Annotation").

Maintained by Joan Garriga. Last updated 1 years ago.

cpp

3.3 match 3.63 score 43 scripts

jtextor

celltrackR:Motion Trajectory Analysis

Methods for analyzing (cell) motion in two or three dimensions. Available measures include displacement, confinement ratio, autocorrelation, straightness, turning angle, and fractal dimension. Measures can be applied to entire tracks, steps, or subtracks with varying length. While the methodology has been developed for cell trajectory analysis, it is applicable to anything that moves including animals, people, or vehicles. Some of the methodology implemented in this packages was described by: Beauchemin, Dixit, and Perelson (2007) <doi:10.4049/jimmunol.178.9.5505>, Beltman, Maree, and de Boer (2009) <doi:10.1038/nri2638>, Gneiting and Schlather (2004) <doi:10.1137/S0036144501394387>, Mokhtari, Mech, Zitzmann, Hasenberg, Gunzer, and Figge (2013) <doi:10.1371/journal.pone.0080808>, Moreau, Lemaitre, Terriac, Azar, Piel, Lennon-Dumenil, and Bousso (2012) <doi:10.1016/j.immuni.2012.05.014>, Textor, Peixoto, Henrickson, Sinn, von Andrian, and Westermann (2011) <doi:10.1073/pnas.1102288108>, Textor, Sinn, and de Boer (2013) <doi:10.1186/1471-2105-14-S6-S10>, Textor, Henrickson, Mandl, von Andrian, Westermann, de Boer, and Beltman (2014) <doi:10.1371/journal.pcbi.1003752>.

Maintained by Johannes Textor. Last updated 7 months ago.

3.8 match 3.08 score 6 scripts

duct317

scDHA:Single-Cell Decomposition using Hierarchical Autoencoder

Provides a fast and accurate pipeline for single-cell analyses. The 'scDHA' software package can perform clustering, dimension reduction and visualization, classification, and time-trajectory inference on single-cell data (Tran et.al. (2021) <DOI:10.1038/s41467-021-21312-2>).

Maintained by Ha Nguyen. Last updated 11 months ago.

cpp

1.8 match 40 stars 6.38 score 20 scripts 2 dependents

crp2a

BayLum:Chronological Bayesian Models Integrating Optically Stimulated Luminescence and Radiocarbon Age Dating

Bayesian analysis of luminescence data and C-14 age estimates. Bayesian models are based on the following publications: Combes, B. & Philippe, A. (2017) <doi:10.1016/j.quageo.2017.02.003> and Combes et al (2015) <doi:10.1016/j.quageo.2015.04.001>. This includes, amongst others, data import, export, application of age models and palaeodose model.

Maintained by Anne Philippe. Last updated 11 months ago.

archaeometry bayesian-statistics geochronology luminescence-dating radiocarbon-dates jags cpp

1.8 match 9 stars 6.52 score 37 scripts

jonesor

mpmsim:Simulation of Matrix Population Models with Defined Life History Characteristics

Allows users to simulate matrix population models with particular characteristics based on aspects of life history such as mortality trajectories and fertility trajectories. Also allows the exploration of sampling error due to small sample size.

Maintained by Owen Jones. Last updated 10 days ago.

1.9 match 5 stars 6.03 score 16 scripts

steps-dev

steps:Spatially- and Temporally-Explicit Population Simulator

Software to simulate population change across space and time. Visintin et al. (2020) <doi:10.1111/2041-210X.13354>.

Maintained by Casey Visintin. Last updated 1 years ago.

meta-population-models cpp

1.7 match 18 stars 6.66 score 84 scripts

siacus

labstatR:Libreria Del Laboratorio Di Statistica Con R

Insieme di funzioni di supporto al volume "Laboratorio di Statistica con R", Iacus-Masarotto, MacGraw-Hill Italia, 2006. This package contains sets of functions defined in "Laboratorio di Statistica con R", Iacus-Masarotto, MacGraw-Hill Italia, 2006. Function names and docs are in italian as well.

Maintained by Stefano M. Iacus. Last updated 3 years ago.

3.0 match 3.79 score 41 scripts 1 dependents

bioc

miaViz:Microbiome Analysis Plotting and Visualization

The miaViz package implements functions to visualize TreeSummarizedExperiment objects especially in the context of microbiome analysis. Part of the mia family of R/Bioconductor packages.

Maintained by Tuomas Borman. Last updated 3 days ago.

microbiome software visualization bioconductor microbiome-analysis plotting

1.3 match 10 stars 8.65 score 81 scripts 1 dependents

skranz

synthdid:Synthetic Difference-in-Difference Estimation

Estimate average treatment effects in panel data. Currently provides methods only for the case that all treated units adopt treatment at the same time.

Maintained by David A. Hirshberg. Last updated 4 years ago.

3.1 match 3.40 score 84 scripts 1 dependents

revbayes

RevGadgets:Visualization and Post-Processing of 'RevBayes' Analyses

Processes and visualizes the output of complex phylogenetic analyses from the 'RevBayes' phylogenetic graphical modeling software.

Maintained by Carrie Tribble. Last updated 1 years ago.

1.8 match 13 stars 6.09 score 208 scripts

gefeizhang

statVisual:Statistical Visualization Tools

Visualization functions in the applications of translational medicine (TM) and biomarker (BM) development to compare groups by statistically visualizing data and/or results of analyses, such as visualizing data by displaying in one figure different groups' histograms, boxplots, densities, scatter plots, error-bar plots, or trajectory plots, by displaying scatter plots of top principal components or dendrograms with data points colored based on group information, or visualizing volcano plots to check the results of whole genome analyses for gene differential expression.

Maintained by Wenfei Zhang. Last updated 5 years ago.

3.5 match 3.00 score 3 scripts

ternaustralia

ausplotsR:TERN AusPlots Australian Ecosystem Monitoring Data

Extraction, preparation, visualisation and analysis of TERN AusPlots ecosystem monitoring data. Direct access to plot-based data on vegetation and soils across Australia, including physical sample barcode numbers. Simple function calls extract the data and merge them into species occurrence matrices for downstream analysis, or calculate things like basal area and fractional cover. TERN AusPlots is a national field plot-based ecosystem surveillance monitoring method and dataset for Australia. The data have been collected across a national network of plots and transects by the Terrestrial Ecosystem Research Network (TERN - <https://www.tern.org.au>), an Australian Government NCRIS-enabled project, and its Ecosystem Surveillance platform (<https://www.tern.org.au/tern-land-observatory/ecosystem-surveillance-and-environmental-monitoring/>).

Maintained by Greg Guerin. Last updated 1 years ago.

1.7 match 10 stars 6.07 score 59 scripts

pik-piam

mrremind:MadRat REMIND Input Data Package

The mrremind packages contains data preprocessing for the REMIND model.

Maintained by Lavinia Baumstark. Last updated 10 hours ago.

1.7 match 4 stars 6.26 score 15 scripts 1 dependents

usaid-oha-si

mindthegap:Mind the Gap

Package to tidy UNAIDS estimates (from the EDMS database) as well as plot trends in UNAIDS 95 goals and ART coverage gap by country.

Maintained by Karishma Srikanth. Last updated 2 months ago.

1.9 match 5 stars 5.51 score 13 scripts

hkestler

BoolNet:Construction, Simulation and Analysis of Boolean Networks

Functions to reconstruct, generate, and simulate synchronous, asynchronous, probabilistic, and temporal Boolean networks. Provides also functions to analyze and visualize attractors in Boolean networks <doi:10.1093/bioinformatics/btq124>.

Maintained by Hans A. Kestler. Last updated 1 years ago.

1.8 match 3 stars 5.90 score 122 scripts 6 dependents

eurocontrol

eurocontrol:Helper functions for EUROCONTROL useRs

The helper functions in this package are designed to make it easy, homogeneus and transparent to perform common tasks usually needed by data analysts and useRs in EUROCONTROL.

Maintained by Enrico Spinielli. Last updated 5 months ago.

3.6 match 1 stars 2.85 score 11 scripts

kopperud

slouch:Stochastic Linear Ornstein-Uhlenbeck Comparative Hypotheses

An implementation of a phylogenetic comparative method. It can fit univariate among-species Ornstein-Uhlenbeck models of phenotypic trait evolution, where the trait evolves towards a primary optimum. The optimum can be modelled as a single parameter, as multiple discrete regimes on the phylogenetic tree, and/or with continuous covariates. See also Hansen (1997) <doi:10.2307/2411186>, Butler & King (2004) <doi:10.1086/426002>, Hansen et al. (2008) <doi:10.1111/j.1558-5646.2008.00412.x>.

Maintained by Bjørn Tore Kopperud. Last updated 1 years ago.

2.0 match 2 stars 5.12 score 44 scripts 1 dependents

maximeherve

RVAideMemoire:Testing and Plotting Procedures for Biostatistics

Contains miscellaneous functions useful in biostatistics, mostly univariate and multivariate testing procedures with a special emphasis on permutation tests. Many functions intend to simplify user's life by shortening existing procedures or by implementing plotting functions that can be used with as many methods from different packages as possible.

Maintained by Maxime HERVE. Last updated 1 years ago.

1.9 match 8 stars 5.31 score 632 scripts

daniellemccool

topdowntimeratio:Top-Down Time Ratio Segmentation for Coordinate Trajectories

Data collected on movement behavior is often in the form of time- stamped latitude/longitude coordinates sampled from the underlying movement behavior. These data can be compressed into a set of segments via the Top- Down Time Ratio Segmentation method described in Meratnia and de By (2004) <doi:10.1007/978-3-540-24741-8_44> which, with some loss of information, can both reduce the size of the data as well as provide corrective smoothing mechanisms to help reduce the impact of measurement error. This is an improvement on the well-known Douglas-Peucker algorithm for segmentation that operates not on the basis of perpendicular distances. Top-Down Time Ratio segmentation allows for disparate sampling time intervals by calculating the distance between locations and segments with respect to time. Provided a trajectory with timestamps, tdtr() returns a set of straight- line segments that can represent the full trajectory. McCool, Lugtig, and Schouten (2022) <doi:10.1007/s11116-022-10328-2> describe this method as implemented here in more detail.

Maintained by Danielle McCool. Last updated 2 years ago.

3.7 match 2.70 score 4 scripts

rafael-ayala

openSkies:Retrieval, Analysis and Visualization of Air Traffic Data

Provides functionalities and data structures to retrieve, analyze and visualize aviation data. It includes a client interface to the 'OpenSky' API <https://opensky-network.org>. It allows retrieval of flight information, as well as aircraft state vectors.

Maintained by Rafael Ayala. Last updated 12 months ago.

1.8 match 11 stars 5.60 score 36 scripts

bioc

condiments:Differential Topology, Progression and Differentiation

This package encapsulate many functions to conduct a differential topology analysis. It focuses on analyzing an 'omic dataset with multiple conditions. While the package is mostly geared toward scRNASeq, it does not place any restriction on the actual input format.

Maintained by Hector Roux de Bezieux. Last updated 3 months ago.

rnaseq sequencing software singlecell transcriptomics multiplecomparison visualization

1.5 match 26 stars 6.52 score 17 scripts

tmsalab

hmcdm:Hidden Markov Cognitive Diagnosis Models for Learning

Fitting hidden Markov models of learning under the cognitive diagnosis framework. The estimation of the hidden Markov diagnostic classification model, the first order hidden Markov model, the reduced-reparameterized unified learning model, and the joint learning model for responses and response times.

Maintained by Sunbeom Kwon. Last updated 2 years ago.

cognitive-diagnostic-models psychometrics rcpp rcpparmadillo openblas cpp openmp

1.7 match 7 stars 5.70 score 12 scripts

cran

astrochron:A Computational Tool for Astrochronology

Routines for astrochronologic testing, astronomical time scale construction, and time series analysis <doi:10.1016/j.earscirev.2018.11.015>. Also included are a range of statistical analysis and modeling routines that are relevant to time scale development and paleoclimate analysis.

Maintained by Stephen Meyers. Last updated 6 months ago.

fortran

3.4 match 5 stars 2.70 score

antcalcagni

ssMousetrack:Bayesian State-Space Modeling of Mouse-Tracking Experiments via Stan

Estimates previously compiled state-space modeling for mouse-tracking experiments using the 'rstan' package, which provides the R interface to the Stan C++ library for Bayesian estimation.

Maintained by Antonio Calcagnì. Last updated 1 days ago.

bayesian-data-analysis mouse-tracking state-space-model cpp

3.4 match 2.70 score 8 scripts

rjacobucci

regsem:Regularized Structural Equation Modeling

Uses both ridge and lasso penalties (and extensions) to penalize specific parameters in structural equation models. The package offers additional cost functions, cross validation, and other extensions beyond traditional structural equation models. Also contains a function to perform exploratory mediation (XMed).

Maintained by Ross Jacobucci. Last updated 2 years ago.

openblas cpp

1.3 match 14 stars 6.63 score 77 scripts

marjoleinbruijning

trackdem:Particle Tracking and Demography

Obtain population density and body size structure, using video material or image sequences as input. Functions assist in the creation of image sequences from videos, background detection and subtraction, particle identification and tracking. An artificial neural network can be trained for noise filtering. The goal is to supply accurate estimates of population size, structure and/or individual behavior, for use in evolutionary and ecological studies.

Maintained by Marjolein Bruijning. Last updated 3 years ago.

cpp

1.8 match 10 stars 4.88 score 15 scripts

jcc9

tempR:Temporal Sensory Data Analysis

Analysis and visualization of data from temporal sensory methods, including for temporal check-all-that-apply (TCATA) and temporal dominance of sensations (TDS). Methods are mainly from manuscripts by Castura, J.C., Antúnez, L., Giménez, A., and Ares, G. (2016) <doi:10.1016/j.foodqual.2015.06.017>, Castura, Baker, and Ross (2016) <doi:10.1016/j.foodqual.2016.06.011>, and Pineau et al. (2009) <doi:10.1016/j.foodqual.2009.04.005>.

Maintained by J.C. Castura. Last updated 10 months ago.

3.9 match 1 stars 2.17 score 37 scripts

uncertaintyquantification

FastGaSP:Fast and Exact Computation of Gaussian Stochastic Process

Implements fast and exact computation of Gaussian stochastic process with the Matern kernel using forward filtering and backward smoothing algorithm. It includes efficient implementations of the inverse Kalman filter, with applications such as estimating particle interaction functions. These tools support models with or without noise. Additionally, the package offers algorithms for fast parameter estimation in latent factor models, where the factor loading matrix is orthogonal, and latent processes are modeled by Gaussian processes. See the references: 1) Mengyang Gu and Yanxun Xu (2020), Journal of Computational and Graphical Statistics; 2) Xinyi Fang and Mengyang Gu (2024), <doi:10.48550/arXiv.2407.10089>; 3) Mengyang Gu and Weining Shen (2020), Journal of Machine Learning Research; 4) Yizi Lin, Xubo Liu, Paul Segall and Mengyang Gu (2025), <doi:10.48550/arXiv.2501.01324>.

Maintained by Mengyang Gu. Last updated 1 months ago.

cpp

3.9 match 2.18 score 25 scripts 1 dependents

r-forge

colorspace:A Toolbox for Manipulating and Assessing Colors and Palettes

Carries out mapping between assorted color spaces including RGB, HSV, HLS, CIEXYZ, CIELUV, HCL (polar CIELUV), CIELAB, and polar CIELAB. Qualitative, sequential, and diverging color palettes based on HCL colors are provided along with corresponding ggplot2 color scales. Color palette choice is aided by an interactive app (with either a Tcl/Tk or a shiny graphical user interface) and shiny apps with an HCL color picker and a color vision deficiency emulator. Plotting functions for displaying and assessing palettes include color swatches, visualizations of the HCL space, and trajectories in HCL and/or RGB spectrum. Color manipulation functions include: desaturation, lightening/darkening, mixing, and simulation of color vision deficiencies (deutanomaly, protanomaly, tritanomaly). Details can be found on the project web page at <https://colorspace.R-Forge.R-project.org/> and in the accompanying scientific paper: Zeileis et al. (2020, Journal of Statistical Software, <doi:10.18637/jss.v096.i01>).

Maintained by Achim Zeileis. Last updated 4 months ago.

0.5 match 16.23 score 8.2k scripts 8.1k dependents