R-universe search: needs:deSolve

indrajeetpatil

ggstatsplot:'ggplot2' Based Plots with Statistical Details

Extension of 'ggplot2', 'ggstatsplot' creates graphics with details from statistical tests included in the plots themselves. It provides an easier syntax to generate information-rich plots for statistical analysis of continuous (violin plots, scatterplots, histograms, dot plots, dot-and-whisker plots) or categorical (pie and bar charts) data. Currently, it supports the most common types of statistical approaches and tests: parametric, nonparametric, robust, and Bayesian versions of t-test/ANOVA, correlation analyses, contingency table analysis, meta-analysis, and regression analyses. References: Patil (2021) <doi:10.21105/joss.03236>.

Maintained by Indrajeet Patil. Last updated 1 months ago.

bayes-factors datascience dataviz effect-size ggplot-extension hypothesis-testing non-parametric-statistics regression-models statistical-analysis

2.1k stars 14.46 score 3.0k scripts 1 dependents

richarddmorey

BayesFactor:Computation of Bayes Factors for Common Designs

A suite of functions for computing various Bayes factors for simple designs, including contingency tables, one- and two-sample designs, one-way designs, general ANOVA designs, and linear regression.

Maintained by Richard D. Morey. Last updated 1 years ago.

cpp

132 stars 13.71 score 1.7k scripts 21 dependents

chjackson

flexsurv:Flexible Parametric Survival and Multi-State Models

Flexible parametric models for time-to-event data, including the Royston-Parmar spline model, generalized gamma and generalized F distributions. Any user-defined parametric distribution can be fitted, given at least an R function defining the probability density or hazard. There are also tools for fitting and predicting from fully parametric multi-state models, based on either cause-specific hazards or mixture models.

Maintained by Christopher Jackson. Last updated 2 months ago.

cpp

57 stars 13.31 score 632 scripts 43 dependents

jamesramsay5

fda:Functional Data Analysis

These functions were developed to support functional data analysis as described in Ramsay, J. O. and Silverman, B. W. (2005) Functional Data Analysis. New York: Springer and in Ramsay, J. O., Hooker, Giles, and Graves, Spencer (2009). Functional Data Analysis with R and Matlab (Springer). The package includes data sets and script files working many examples including all but one of the 76 figures in this latter book. Matlab versions are available by ftp from <https://www.psych.mcgill.ca/misc/fda/downloads/FDAfuns/>.

Maintained by James Ramsay. Last updated 4 months ago.

3 stars 11.88 score 2.0k scripts 142 dependents

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 10 days 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

114 stars 11.74 score 1.3k scripts 4 dependents

epimodel

EpiModel:Mathematical Modeling of Infectious Disease Dynamics

Tools for simulating mathematical models of infectious disease dynamics. Epidemic model classes include deterministic compartmental models, stochastic individual-contact models, and stochastic network models. Network models use the robust statistical methods of exponential-family random graph models (ERGMs) from the Statnet suite of software packages in R. Standard templates for epidemic modeling include SI, SIR, and SIS disease types. EpiModel features an API for extending these templates to address novel scientific research aims. Full methods for EpiModel are detailed in Jenness et al. (2018, <doi:10.18637/jss.v084.i08>).

Maintained by Samuel Jenness. Last updated 2 months ago.

agent-based-modeling epidemics epidemiology infectious-diseases network-graph cpp

250 stars 11.43 score 315 scripts

indrajeetpatil

statsExpressions:Tidy Dataframes and Expressions with Statistical Details

Utilities for producing dataframes with rich details for the most common types of statistical approaches and tests: parametric, nonparametric, robust, and Bayesian t-test, one-way ANOVA, correlation analyses, contingency table analyses, and meta-analyses. The functions are pipe-friendly and provide a consistent syntax to work with tidy data. These dataframes additionally contain expressions with statistical details, and can be used in graphing packages. This package also forms the statistical processing backend for 'ggstatsplot'. References: Patil (2021) <doi:10.21105/joss.03236>.

Maintained by Indrajeet Patil. Last updated 1 months ago.

bayesian-inference bayesian-statistics contingency-table correlation effectsize meta-analysis parametric robust robust-statistics statistical-details statistical-tests tidy

312 stars 10.92 score 146 scripts 2 dependents

ndphillips

yarrr:A Companion to the e-Book "YaRrr!: The Pirate's Guide to R"

Contains a mixture of functions and data sets referred to in the introductory e-book "YaRrr!: The Pirate's Guide to R". The latest version of the e-book is available for free at <https://www.thepiratesguidetor.com>.

Maintained by Nathaniel Phillips. Last updated 12 months ago.

78 stars 10.67 score 1.2k scripts 2 dependents

matthieustigler

tsDyn:Nonlinear Time Series Models with Regime Switching

Implements nonlinear autoregressive (AR) time series models. For univariate series, a non-parametric approach is available through additive nonlinear AR. Parametric modeling and testing for regime switching dynamics is available when the transition is either direct (TAR: threshold AR) or smooth (STAR: smooth transition AR, LSTAR). For multivariate series, one can estimate a range of TVAR or threshold cointegration TVECM models with two or three regimes. Tests can be conducted for TVAR as well as for TVECM (Hansen and Seo 2002 and Seo 2006).

Maintained by Matthieu Stigler. Last updated 5 months ago.

34 stars 10.53 score 684 scripts 3 dependents

usepa

httk:High-Throughput Toxicokinetics

Pre-made models that can be rapidly tailored to various chemicals and species using chemical-specific in vitro data and physiological information. These tools allow incorporation of chemical toxicokinetics ("TK") and in vitro-in vivo extrapolation ("IVIVE") into bioinformatics, as described by Pearce et al. (2017) (<doi:10.18637/jss.v079.i04>). Chemical-specific in vitro data characterizing toxicokinetics have been obtained from relatively high-throughput experiments. The chemical-independent ("generic") physiologically-based ("PBTK") and empirical (for example, one compartment) "TK" models included here can be parameterized with in vitro data or in silico predictions which are provided for thousands of chemicals, multiple exposure routes, and various species. High throughput toxicokinetics ("HTTK") is the combination of in vitro data and generic models. We establish the expected accuracy of HTTK for chemicals without in vivo data through statistical evaluation of HTTK predictions for chemicals where in vivo data do exist. The models are systems of ordinary differential equations that are developed in MCSim and solved using compiled (C-based) code for speed. A Monte Carlo sampler is included for simulating human biological variability (Ring et al., 2017 <doi:10.1016/j.envint.2017.06.004>) and propagating parameter uncertainty (Wambaugh et al., 2019 <doi:10.1093/toxsci/kfz205>). Empirically calibrated methods are included for predicting tissue:plasma partition coefficients and volume of distribution (Pearce et al., 2017 <doi:10.1007/s10928-017-9548-7>). These functions and data provide a set of tools for using IVIVE to convert concentrations from high-throughput screening experiments (for example, Tox21, ToxCast) to real-world exposures via reverse dosimetry (also known as "RTK") (Wetmore et al., 2015 <doi:10.1093/toxsci/kfv171>).

Maintained by John Wambaugh. Last updated 2 months ago.

comptox ord

27 stars 10.22 score 307 scripts 1 dependents

refunders

refund:Regression with Functional Data

Methods for regression for functional data, including function-on-scalar, scalar-on-function, and function-on-function regression. Some of the functions are applicable to image data.

Maintained by Julia Wrobel. Last updated 6 months ago.

43 stars 10.11 score 472 scripts 17 dependents

mrc-ide

odin:ODE Generation and Integration

Generate systems of ordinary differential equations (ODE) and integrate them, using a domain specific language (DSL). The DSL uses R's syntax, but compiles to C in order to efficiently solve the system. A solver is not provided, but instead interfaces to the packages 'deSolve' and 'dde' are generated. With these, while solving the differential equations, no allocations are done and the calculations remain entirely in compiled code. Alternatively, a model can be transpiled to R for use in contexts where a C compiler is not present. After compilation, models can be inspected to return information about parameters and outputs, or intermediate values after calculations. 'odin' is not targeted at any particular domain and is suitable for any system that can be expressed primarily as mathematical expressions. Additional support is provided for working with delays (delay differential equations, DDE), using interpolated functions during interpolation, and for integrating quantities that represent arrays.

Maintained by Rich FitzJohn. Last updated 9 months ago.

infrastructure

106 stars 9.74 score 290 scripts 3 dependents

moviedo5

fda.usc:Functional Data Analysis and Utilities for Statistical Computing

Routines for exploratory and descriptive analysis of functional data such as depth measurements, atypical curves detection, regression models, supervised classification, unsupervised classification and functional analysis of variance.

Maintained by Manuel Oviedo de la Fuente. Last updated 5 months ago.

functional-data-analysis fortran

12 stars 9.72 score 560 scripts 22 dependents

jamovi

jmv:The 'jamovi' Analyses

A suite of common statistical methods such as descriptives, t-tests, ANOVAs, regression, correlation matrices, proportion tests, contingency tables, and factor analysis. This package is also useable from the 'jamovi' statistical spreadsheet (see <https://www.jamovi.org> for more information).

Maintained by Jonathon Love. Last updated 27 days ago.

59 stars 9.58 score 440 scripts

sizespectrum

mizer:Dynamic Multi-Species Size Spectrum Modelling

A set of classes and methods to set up and run multi-species, trait based and community size spectrum ecological models, focused on the marine environment.

Maintained by Gustav Delius. Last updated 2 months ago.

ecosystem-model fish-population-dynamics fisheries fisheries-management marine-ecosystem population-dynamics simulation size-structure species-interactions transport-equation cpp

39 stars 9.41 score 207 scripts

sbegueria

SPEI:Calculation of the Standardized Precipitation-Evapotranspiration Index

A set of functions for computing potential evapotranspiration and several widely used drought indices including the Standardized Precipitation-Evapotranspiration Index (SPEI).

Maintained by Santiago Beguería. Last updated 2 years ago.

82 stars 9.27 score 314 scripts 20 dependents

matthias-da

robCompositions:Compositional Data Analysis

Methods for analysis of compositional data including robust methods (<doi:10.1007/978-3-319-96422-5>), imputation of missing values (<doi:10.1016/j.csda.2009.11.023>), methods to replace rounded zeros (<doi:10.1080/02664763.2017.1410524>, <doi:10.1016/j.chemolab.2016.04.011>, <doi:10.1016/j.csda.2012.02.012>), count zeros (<doi:10.1177/1471082X14535524>), methods to deal with essential zeros (<doi:10.1080/02664763.2016.1182135>), (robust) outlier detection for compositional data, (robust) principal component analysis for compositional data, (robust) factor analysis for compositional data, (robust) discriminant analysis for compositional data (Fisher rule), robust regression with compositional predictors, functional data analysis (<doi:10.1016/j.csda.2015.07.007>) and p-splines (<doi:10.1016/j.csda.2015.07.007>), contingency (<doi:10.1080/03610926.2013.824980>) and compositional tables (<doi:10.1111/sjos.12326>, <doi:10.1111/sjos.12223>, <doi:10.1080/02664763.2013.856871>) and (robust) Anderson-Darling normality tests for compositional data as well as popular log-ratio transformations (addLR, cenLR, isomLR, and their inverse transformations). In addition, visualisation and diagnostic tools are implemented as well as high and low-level plot functions for the ternary diagram.

Maintained by Matthias Templ. Last updated 1 months ago.

cpp

11 stars 9.21 score 226 scripts 2 dependents

robinhankin

hypergeo:The Gauss Hypergeometric Function

The Gaussian hypergeometric function for complex numbers.

Maintained by Robin K. S. Hankin. Last updated 6 days ago.

cpp

2 stars 8.97 score 109 scripts 77 dependents

oakleyj

SHELF:Tools to Support the Sheffield Elicitation Framework

Implements various methods for eliciting a probability distribution for a single parameter from an expert or a group of experts. The expert provides a small number of probability judgements, corresponding to points on his or her cumulative distribution function. A range of parametric distributions can then be fitted and displayed, with feedback provided in the form of fitted probabilities and percentiles. For multiple experts, a weighted linear pool can be calculated. Also includes functions for eliciting beliefs about population distributions; eliciting multivariate distributions using a Gaussian copula; eliciting a Dirichlet distribution; eliciting distributions for variance parameters in a random effects meta-analysis model; survival extrapolation. R Shiny apps for most of the methods are included.

Maintained by Jeremy Oakley. Last updated 28 days ago.

19 stars 8.90 score 73 scripts 3 dependents

r-forge

FME:A Flexible Modelling Environment for Inverse Modelling, Sensitivity, Identifiability and Monte Carlo Analysis

Provides functions to help in fitting models to data, to perform Monte Carlo, sensitivity and identifiability analysis. It is intended to work with models be written as a set of differential equations that are solved either by an integration routine from package 'deSolve', or a steady-state solver from package 'rootSolve'. However, the methods can also be used with other types of functions.

Maintained by Karline Soetaert. Last updated 2 years ago.

fortran

8.62 score 382 scripts 9 dependents

rsetienne

DAISIE:Dynamical Assembly of Islands by Speciation, Immigration and Extinction

Simulates and computes the (maximum) likelihood of a dynamical model of island biota assembly through speciation, immigration and extinction. See Valente et al. (2015) <doi:10.1111/ele.12461>.

Maintained by Rampal S. Etienne. Last updated 2 months ago.

fortran cpp

9 stars 8.59 score 55 scripts 1 dependents

hmorlon

RPANDA:Phylogenetic ANalyses of DiversificAtion

Implements macroevolutionary analyses on phylogenetic trees. See Morlon et al. (2010) <DOI:10.1371/journal.pbio.1000493>, Morlon et al. (2011) <DOI:10.1073/pnas.1102543108>, Condamine et al. (2013) <DOI:10.1111/ele.12062>, Morlon et al. (2014) <DOI:10.1111/ele.12251>, Manceau et al. (2015) <DOI:10.1111/ele.12415>, Lewitus & Morlon (2016) <DOI:10.1093/sysbio/syv116>, Drury et al. (2016) <DOI:10.1093/sysbio/syw020>, Manceau et al. (2016) <DOI:10.1093/sysbio/syw115>, Morlon et al. (2016) <DOI:10.1111/2041-210X.12526>, Clavel & Morlon (2017) <DOI:10.1073/pnas.1606868114>, Drury et al. (2017) <DOI:10.1093/sysbio/syx079>, Lewitus & Morlon (2017) <DOI:10.1093/sysbio/syx095>, Drury et al. (2018) <DOI:10.1371/journal.pbio.2003563>, Clavel et al. (2019) <DOI:10.1093/sysbio/syy045>, Maliet et al. (2019) <DOI:10.1038/s41559-019-0908-0>, Billaud et al. (2019) <DOI:10.1093/sysbio/syz057>, Lewitus et al. (2019) <DOI:10.1093/sysbio/syz061>, Aristide & Morlon (2019) <DOI:10.1111/ele.13385>, Maliet et al. (2020) <DOI:10.1111/ele.13592>, Drury et al. (2021) <DOI:10.1371/journal.pbio.3001270>, Perez-Lamarque & Morlon (2022) <DOI:10.1111/mec.16478>, Perez-Lamarque et al. (2022) <DOI:10.1101/2021.08.30.458192>, Mazet et al. (2023) <DOI:10.1111/2041-210X.14195>, Drury et al. (2024) <DOI:10.1016/j.cub.2023.12.055>.

Maintained by Hélène Morlon. Last updated 3 months ago.

24 stars 8.50 score 255 scripts

richfitz

diversitree:Comparative 'Phylogenetic' Analyses of Diversification

Contains a number of comparative 'phylogenetic' methods, mostly focusing on analysing diversification and character evolution. Contains implementations of 'BiSSE' (Binary State 'Speciation' and Extinction) and its unresolved tree extensions, 'MuSSE' (Multiple State 'Speciation' and Extinction), 'QuaSSE', 'GeoSSE', and 'BiSSE-ness' Other included methods include Markov models of discrete and continuous trait evolution and constant rate 'speciation' and extinction.

Maintained by Richard G. FitzJohn. Last updated 6 months ago.

fftw3 gsl openblas cpp

33 stars 8.50 score 524 scripts 4 dependents

thej022214

hisse:Hidden State Speciation and Extinction

Sets up and executes a HiSSE model (Hidden State Speciation and Extinction) on a phylogeny and character sets to test for hidden shifts in trait dependent rates of diversification. Beaulieu and O'Meara (2016) <doi:10.1093/sysbio/syw022>.

Maintained by Jeremy Beaulieu. Last updated 2 months ago.

6 stars 8.45 score 152 scripts

thej022214

OUwie:Analysis of Evolutionary Rates in an OU Framework

Estimates rates for continuous character evolution under Brownian motion and a new set of Ornstein-Uhlenbeck based Hansen models that allow both the strength of the pull and stochastic motion to vary across selective regimes. Beaulieu et al (2012).

Maintained by Jeremy Beaulieu. Last updated 12 days ago.

9 stars 8.42 score 161 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 23 days ago.

20 stars 8.35 score 251 scripts

bioc

flowStats:Statistical methods for the analysis of flow cytometry data

Methods and functionality to analyse flow data that is beyond the basic infrastructure provided by the flowCore package.

Maintained by Greg Finak. Last updated 5 months ago.

immunooncology flowcytometry cellbasedassays

14 stars 8.27 score 195 scripts 1 dependents

robjhyndman

demography:Forecasting Mortality, Fertility, Migration and Population Data

Functions for demographic analysis including lifetable calculations; Lee-Carter modelling; functional data analysis of mortality rates, fertility rates, net migration numbers; and stochastic population forecasting.

Maintained by Rob Hyndman. Last updated 4 months ago.

actuarial demography forecasting

74 stars 8.21 score 241 scripts 6 dependents

daijiang

hillR:Diversity Through Hill Numbers

Calculate taxonomic, functional and phylogenetic diversity measures through Hill Numbers proposed by Chao, Chiu and Jost (2014) <doi:10.1146/annurev-ecolsys-120213-091540>.

Maintained by Daijiang Li. Last updated 11 months ago.

biodiversity hill-numbers

33 stars 8.21 score 157 scripts 3 dependents

jranke

mkin:Kinetic Evaluation of Chemical Degradation Data

Calculation routines based on the FOCUS Kinetics Report (2006, 2014). Includes a function for conveniently defining differential equation models, model solution based on eigenvalues if possible or using numerical solvers. If a C compiler (on windows: 'Rtools') is installed, differential equation models are solved using automatically generated C functions. Non-constant errors can be taken into account using variance by variable or two-component error models <doi:10.3390/environments6120124>. Hierarchical degradation models can be fitted using nonlinear mixed-effects model packages as a back end <doi:10.3390/environments8080071>. Please note that no warranty is implied for correctness of results or fitness for a particular purpose.

Maintained by Johannes Ranke. Last updated 1 months ago.

degradation focus-kinetics kinetic-models kinetics ode ode-model

11 stars 8.18 score 78 scripts 1 dependents

hesim-dev

hesim:Health Economic Simulation Modeling and Decision Analysis

A modular and computationally efficient R package for parameterizing, simulating, and analyzing health economic simulation models. The package supports cohort discrete time state transition models (Briggs et al. 1998) <doi:10.2165/00019053-199813040-00003>, N-state partitioned survival models (Glasziou et al. 1990) <doi:10.1002/sim.4780091106>, and individual-level continuous time state transition models (Siebert et al. 2012) <doi:10.1016/j.jval.2012.06.014>, encompassing both Markov (time-homogeneous and time-inhomogeneous) and semi-Markov processes. Decision uncertainty from a cost-effectiveness analysis is quantified with standard graphical and tabular summaries of a probabilistic sensitivity analysis (Claxton et al. 2005, Barton et al. 2008) <doi:10.1002/hec.985>, <doi:10.1111/j.1524-4733.2008.00358.x>. Use of C++ and data.table make individual-patient simulation, probabilistic sensitivity analysis, and incorporation of patient heterogeneity fast.

Maintained by Devin Incerti. Last updated 6 months ago.

health-economic-evaluation microsimulation simulation-modeling cpp

67 stars 8.12 score 41 scripts

sbgraves237

Ecfun:Functions for 'Ecdat'

Functions and vignettes to update data sets in 'Ecdat' and to create, manipulate, plot, and analyze those and similar data sets.

Maintained by Spencer Graves. Last updated 4 months ago.

8.02 score 85 scripts 4 dependents

danheck

TreeBUGS:Hierarchical Multinomial Processing Tree Modeling

User-friendly analysis of hierarchical multinomial processing tree (MPT) models that are often used in cognitive psychology. Implements the latent-trait MPT approach (Klauer, 2010) <DOI:10.1007/s11336-009-9141-0> and the beta-MPT approach (Smith & Batchelder, 2010) <DOI:10.1016/j.jmp.2009.06.007> to model heterogeneity of participants. MPT models are conveniently specified by an .eqn-file as used by other MPT software and data are provided by a .csv-file or directly in R. Models are either fitted by calling JAGS or by an MPT-tailored Gibbs sampler in C++ (only for nonhierarchical and beta MPT models). Provides tests of heterogeneity and MPT-tailored summaries and plotting functions. A detailed documentation is available in Heck, Arnold, & Arnold (2018) <DOI:10.3758/s13428-017-0869-7> and a tutorial on MPT modeling can be found in Schmidt, Erdfelder, & Heck (2023) <DOI:10.1037/met0000561>.

Maintained by Daniel W. Heck. Last updated 17 days ago.

openblas cpp jags

12 stars 8.01 score 53 scripts 1 dependents

lukejharmon

geiger:Analysis of Evolutionary Diversification

Methods for fitting macroevolutionary models to phylogenetic trees Pennell (2014) <doi:10.1093/bioinformatics/btu181>.

Maintained by Luke Harmon. Last updated 2 years ago.

openblas cpp

1 stars 7.84 score 2.3k scripts 28 dependents

statswithr

statsr:Companion Software for the Coursera Statistics with R Specialization

Data and functions to support Bayesian and frequentist inference and decision making for the Coursera Specialization "Statistics with R". See <https://github.com/StatsWithR/statsr> for more information.

Maintained by Merlise Clyde. Last updated 4 years ago.

bayesian-inference coursera statistics

71 stars 7.82 score 880 scripts

valeriapolicastro

robin:ROBustness in Network

Assesses the robustness of the community structure of a network found by one or more community detection algorithm to give indications about their reliability. It detects if the community structure found by a set of algorithms is statistically significant and compares the different selected detection algorithms on the same network. robin helps to choose among different community detection algorithms the one that better fits the network of interest. Reference in Policastro V., Righelli D., Carissimo A., Cutillo L., De Feis I. (2021) <https://journal.r-project.org/archive/2021/RJ-2021-040/index.html>.

Maintained by Valeria Policastro. Last updated 8 days ago.

19 stars 7.72 score 8 scripts

samhforbes

PupillometryR:A Unified Pipeline for Pupillometry Data

Provides a unified pipeline to clean, prepare, plot, and run basic analyses on pupillometry experiments.

Maintained by Samuel Forbes. Last updated 2 years ago.

44 stars 7.58 score 288 scripts 1 dependents

tpetzoldt

growthrates:Estimate Growth Rates from Experimental Data

A collection of methods to determine growth rates from experimental data, in particular from batch experiments and plate reader trials.

Maintained by Thomas Petzoldt. Last updated 2 years ago.

27 stars 7.52 score 102 scripts

isaakiel

mortAAR:Analysis of Archaeological Mortality Data

A collection of functions for the analysis of archaeological mortality data (on the topic see e.g. Chamberlain 2006 <https://books.google.de/books?id=nG5FoO_becAC&lpg=PA27&ots=LG0b_xrx6O&dq=life%20table%20archaeology&pg=PA27#v=onepage&q&f=false>). It takes demographic data in different formats and displays the result in a standard life table as well as plots the relevant indices (percentage of deaths, survivorship, probability of death, life expectancy, percentage of population). It also checks for possible biases in the age structure and applies corrections to life tables.

Maintained by Nils Mueller-Scheessel. Last updated 3 months ago.

anthropology archaeology demography statistics

15 stars 7.49 score 23 scripts

mplatzer

BTYDplus:Probabilistic Models for Assessing and Predicting your Customer Base

Provides advanced statistical methods to describe and predict customers' purchase behavior in a non-contractual setting. It uses historic transaction records to fit a probabilistic model, which then allows to compute quantities of managerial interest on a cohort- as well as on a customer level (Customer Lifetime Value, Customer Equity, P(alive), etc.). This package complements the BTYD package by providing several additional buy-till-you-die models, that have been published in the marketing literature, but whose implementation are complex and non-trivial. These models are: NBD [Ehrenberg (1959) <doi:10.2307/2985810>], MBG/NBD [Batislam et al (2007) <doi:10.1016/j.ijresmar.2006.12.005>], (M)BG/CNBD-k [Reutterer et al (2020) <doi:10.1016/j.ijresmar.2020.09.002>], Pareto/NBD (HB) [Abe (2009) <doi:10.1287/mksc.1090.0502>] and Pareto/GGG [Platzer and Reutterer (2016) <doi:10.1287/mksc.2015.0963>].

Maintained by Michael Platzer. Last updated 12 months ago.

crm customer-behavior marketing-science predictive-analytics cpp

188 stars 7.48 score 64 scripts

dboslab

expowo:An R package for mining global plant diversity and distribution data

Produces diversity estimates and species lists with associated global distribution for any vascular plant family and genus from 'Plants of the World Online' database <https://powo.science.kew.org/>, by interacting with the source code of each plant taxon page. It also creates global maps of species richness, graphics of species discoveries and nomenclatural changes over time. For more details

Maintained by Debora Zuanny. Last updated 5 days ago.

data-mining extractor

8 stars 7.44 score 64 scripts

spatpomp-org

spatPomp:Inference for Spatiotemporal Partially Observed Markov Processes

Inference on panel data using spatiotemporal partially-observed Markov process (SpatPOMP) models. The 'spatPomp' package extends 'pomp' to include algorithms taking advantage of the spatial structure in order to assist with handling high dimensional processes. See Asfaw et al. (2024) <doi:10.48550/arXiv.2101.01157> for further description of the package.

Maintained by Edward Ionides. Last updated 5 months ago.

2 stars 7.38 score 93 scripts

kenaho1

asbio:A Collection of Statistical Tools for Biologists

Contains functions from: Aho, K. (2014) Foundational and Applied Statistics for Biologists using R. CRC/Taylor and Francis, Boca Raton, FL, ISBN: 978-1-4398-7338-0.

Maintained by Ken Aho. Last updated 2 months ago.

5 stars 7.32 score 310 scripts 3 dependents

ibecav

CGPfunctions:Powell Miscellaneous Functions for Teaching and Learning Statistics

Miscellaneous functions useful for teaching statistics as well as actually practicing the art. They typically are not new methods but rather wrappers around either base R or other packages.

Maintained by Chuck Powell. Last updated 4 years ago.

27 stars 7.28 score 122 scripts

coleoguy

evobiR:Evolutionary Biology in R

Comparative analysis of continuous traits influencing discrete states, and utility tools to facilitate comparative analyses. Implementations of ABBA/BABA type statistics to test for introgression in genomic data.

Maintained by Heath Blackmon. Last updated 11 months ago.

15 stars 7.22 score 124 scripts

john-harrold

ubiquity:PKPD, PBPK, and Systems Pharmacology Modeling Tools

Complete work flow for the analysis of pharmacokinetic pharmacodynamic (PKPD), physiologically-based pharmacokinetic (PBPK) and systems pharmacology models including: creation of ordinary differential equation-based models, pooled parameter estimation, individual/population based simulations, rule-based simulations for clinical trial design and modeling assays, deployment with a customizable 'Shiny' app, and non-compartmental analysis. System-specific analysis templates can be generated and each element includes integrated reporting with 'PowerPoint' and 'Word'.

Maintained by John Harrold. Last updated 8 days ago.

modeling pkpd

13 stars 7.14 score 33 scripts

siacus

sde:Simulation and Inference for Stochastic Differential Equations

Companion package to the book Simulation and Inference for Stochastic Differential Equations With R Examples, ISBN 978-0-387-75838-1, Springer, NY. *

Maintained by Stefano Maria Iacus. Last updated 2 years ago.

7.08 score 178 scripts 15 dependents

rsetienne

DDD:Diversity-Dependent Diversification

Implements maximum likelihood and bootstrap methods based on the diversity-dependent birth-death process to test whether speciation or extinction are diversity-dependent, under various models including various types of key innovations. See Etienne et al. 2012, Proc. Roy. Soc. B 279: 1300-1309, <DOI:10.1098/rspb.2011.1439>, Etienne & Haegeman 2012, Am. Nat. 180: E75-E89, <DOI:10.1086/667574>, Etienne et al. 2016. Meth. Ecol. Evol. 7: 1092-1099, <DOI:10.1111/2041-210X.12565> and Laudanno et al. 2021. Syst. Biol. 70: 389–407, <DOI:10.1093/sysbio/syaa048>. Also contains functions to simulate the diversity-dependent process.

Maintained by Rampal S. Etienne. Last updated 4 months ago.

cpp

4 stars 7.00 score 80 scripts 7 dependents

albgarre

biogrowth:Modelling of Population Growth

Modelling of population growth under static and dynamic environmental conditions. Includes functions for model fitting and making prediction under isothermal and dynamic conditions. The methods (algorithms & models) are based on predictive microbiology (See Perez-Rodriguez and Valero (2012, ISBN:978-1-4614-5519-6)).

Maintained by Alberto Garre. Last updated 5 days ago.

6 stars 6.98 score 44 scripts

trenchproject

TrenchR:Tools for Microclimate and Biophysical Ecology

Tools for translating environmental change into organismal response. Microclimate models to vertically scale weather station data to organismal heights. The biophysical modeling tools include both general models for heat flows and specific models to predict body temperatures for a variety of ectothermic taxa. Additional functions model and temporally partition air and soil temperatures and solar radiation. Utility functions estimate the organismal and environmental parameters needed for biophysical ecology. 'TrenchR' focuses on relatively simple and modular functions so users can create transparent and flexible biophysical models. Many functions are derived from Gates (1980) <doi:10.1007/978-1-4612-6024-0> and Campbell and Norman (1988) <isbn:9780387949376>.

Maintained by Lauren Buckley. Last updated 1 years ago.

13 stars 6.89 score 43 scripts

giabaio

survHE:Survival Analysis in Health Economic Evaluation

Contains a suite of functions for survival analysis in health economics. These can be used to run survival models under a frequentist (based on maximum likelihood) or a Bayesian approach (both based on Integrated Nested Laplace Approximation or Hamiltonian Monte Carlo). To run the Bayesian models, the user needs to install additional modules (packages), i.e. 'survHEinla' and 'survHEhmc'. These can be installed using 'remotes::install_github' from their GitHub repositories: (<https://github.com/giabaio/survHEhmc> and <https://github.com/giabaio/survHEinla/> respectively). 'survHEinla' is based on the package INLA, which is available for download at <https://inla.r-inla-download.org/R/stable/>. The user can specify a set of parametric models using a common notation and select the preferred mode of inference. The results can also be post-processed to produce probabilistic sensitivity analysis and can be used to export the output to an Excel file (e.g. for a Markov model, as often done by modellers and practitioners). <doi:10.18637/jss.v095.i14>.

Maintained by Gianluca Baio. Last updated 23 days ago.

frequentist hamiltonian-monte-carlo health-economic-evaluation inla plotting-survival-curves rstan survival-analysis survival-models uncertainty openjdk

42 stars 6.88 score 2 dependents

pik-piam

edgeTransport:Prepare EDGE Transport Data for the REMIND model

EDGE-T is a fork of the GCAM transport module https://jgcri.github.io/gcam-doc/energy.html#transportation with a high level of detail in its representation of technological and modal options. It is a partial equilibrium model with a nested multinomial logit structure and relies on the modified logit formulation. Most of the sources are not publicly available. PIK-internal users can find the sources in the distributed file system in the folder `/p/projects/rd3mod/inputdata/sources/EDGE-Transport-Standalone`.

Maintained by Johanna Hoppe. Last updated 16 hours ago.

5 stars 6.84 score 16 scripts 2 dependents

jrdnmdhl

flexsurvcure:Flexible Parametric Cure Models

Flexible parametric mixture and non-mixture cure models for time-to-event data.

Maintained by Jordan Amdahl. Last updated 1 months ago.

16 stars 6.82 score 20 scripts 2 dependents

joshwlambert

DAISIEprep:Extracts Phylogenetic Island Community Data from Phylogenetic Trees

Extracts colonisation and branching times of island species to be used for analysis in the R package 'DAISIE'. It uses phylogenetic and endemicity data to extract the separate island colonists and store them.

Maintained by Joshua W. Lambert. Last updated 2 months ago.

data-science island-biogeography phylogenetics

6 stars 6.78 score 24 scripts

oucru-modelling

serosv:Model Infectious Disease Parameters from Serosurveys

An easy-to-use and efficient tool to estimate infectious diseases parameters using serological data. Implemented models include SIR models (basic_sir_model(), static_sir_model(), mseir_model(), sir_subpops_model()), parametric models (polynomial_model(), fp_model()), nonparametric models (lp_model()), semiparametric models (penalized_splines_model()), hierarchical models (hierarchical_bayesian_model()). The package is based on the book "Modeling Infectious Disease Parameters Based on Serological and Social Contact Data: A Modern Statistical Perspective" (Hens, Niel & Shkedy, Ziv & Aerts, Marc & Faes, Christel & Damme, Pierre & Beutels, Philippe., 2013) <doi:10.1007/978-1-4614-4072-7>.

Maintained by Anh Phan Truong Quynh. Last updated 9 days ago.

cpp

6.77 score 24 scripts

unina-sfere

funcharts:Functional Control Charts

Provides functional control charts for statistical process monitoring of functional data, using the methods of Capezza et al. (2020) <doi:10.1002/asmb.2507>, Centofanti et al. (2021) <doi:10.1080/00401706.2020.1753581>, Capezza et al. (2024) <doi:10.1080/00401706.2024.2327346>, Capezza et al. (2024) <doi:10.1080/00224065.2024.2383674>, Centofanti et al. (2022) <doi:10.48550/arXiv.2205.06256>. The package is thoroughly illustrated in the paper of Capezza et al (2023) <doi:10.1080/00224065.2023.2219012>.

Maintained by Christian Capezza. Last updated 12 days ago.

openblas cpp

2 stars 6.73 score 168 scripts

mjanuario

evolved:Open Software for Teaching Evolutionary Biology at Multiple Scales Through Virtual Inquiries

"Evolutionary Virtual Education" - 'evolved' - provides multiple tools to help educators (especially at the graduate level or in advanced undergraduate level courses) apply inquiry-based learning in general evolution classes. In particular, the tools provided include functions that simulate evolutionary processes (e.g., genetic drift, natural selection within a single locus) or concepts (e.g. Hardy-Weinberg equilibrium, phylogenetic distribution of traits). More than only simulating, the package also provides tools for students to analyze (e.g., measuring, testing, visualizing) datasets with characteristics that are common to many fields related to evolutionary biology. Importantly, the package is heavily oriented towards providing tools for inquiry-based learning - where students follow scientific practices to actively construct knowledge. For additional details, see package's vignettes.

Maintained by Matheus Januario. Last updated 2 months ago.

3 stars 6.73 score 23 scripts

pik-piam

mrcommons:MadRat commons Input Data Library

Provides useful functions and a common structure to all the input data required to run models like MAgPIE and REMIND of model input data.

Maintained by Jan Philipp Dietrich. Last updated 2 days ago.

1 stars 6.70 score 16 scripts 15 dependents

bioc

miaSim:Microbiome Data Simulation

Microbiome time series simulation with generalized Lotka-Volterra model, Self-Organized Instability (SOI), and other models. Hubbell's Neutral model is used to determine the abundance matrix. The resulting abundance matrix is applied to (Tree)SummarizedExperiment objects.

Maintained by Yagmur Simsek. Last updated 5 months ago.

microbiome software sequencing dnaseq atacseq coverage network

21 stars 6.64 score 23 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

15 stars 6.63 score 94 scripts 1 dependents

jsanchezalv

WARDEN:Workflows for Health Technology Assessments in R using Discrete EveNts

Toolkit to support and perform discrete event simulations without resource constraints in the context of health technology assessments (HTA). The package focuses on cost-effectiveness modelling and aims to be submission-ready to relevant HTA bodies in alignment with 'NICE TSD 15' <https://www.sheffield.ac.uk/nice-dsu/tsds/patient-level-simulation>. More details an examples can be found in the package website <https://jsanchezalv.github.io/WARDEN/>.

Maintained by Javier Sanchez Alvarez. Last updated 3 months ago.

6 stars 6.62 score 9 scripts

gloewing

fastFMM:Fast Functional Mixed Models using Fast Univariate Inference

Implementation of the fast univariate inference approach (Cui et al. (2022) <doi:10.1080/10618600.2021.1950006>, Loewinger et al. (2024) <doi:10.7554/eLife.95802.2>) for fitting functional mixed models. User guides and Python package information can be found at <https://github.com/gloewing/photometry_FLMM>.

Maintained by Erjia Cui. Last updated 5 days ago.

9 stars 6.51 score 22 scripts

mflores72000

ILS:Interlaboratory Study

It performs interlaboratory studies (ILS) to detect those laboratories that provide non-consistent results when comparing to others. It permits to work simultaneously with various testing materials, from standard univariate, and functional data analysis (FDA) perspectives. The univariate approach based on ASTM E691-08 consist of estimating the Mandel's h and k statistics to identify those laboratories that provide more significant different results, testing also the presence of outliers by Cochran and Grubbs tests, Analysis of variance (ANOVA) techniques are provided (F and Tuckey tests) to test differences in means corresponding to different laboratories per each material. Taking into account the functional nature of data retrieved in analytical chemistry, applied physics and engineering (spectra, thermograms, etc.). ILS package provides a FDA approach for finding the Mandel's k and h statistics distribution by smoothing bootstrap resampling.

Maintained by Miguel Flores. Last updated 2 years ago.

6.48 score 75 scripts

jandraor

readsdr:Translate Models from System Dynamics Software into 'R'

The goal of 'readsdr' is to bridge the design capabilities from specialised System Dynamics software with the powerful numerical tools offered by 'R' libraries. The package accomplishes this goal by parsing 'XMILE' files ('Vensim' and 'Stella') models into 'R' objects to construct networks (graph theory); 'ODE' functions for 'Stan'; and inputs to simulate via 'deSolve' as described in Duggan (2016) <doi:10.1007/978-3-319-34043-2>.

Maintained by Jair Andrade. Last updated 10 months ago.

stan system-dynamics

19 stars 6.47 score 62 scripts

pik-piam

mrwater:madrat based MAgPIE water Input Data Library

Provides functions for MAgPIE cellular input data generation and stand-alone water calculations.

Maintained by Felicitas Beier. Last updated 5 months ago.

6.45 score 4 scripts 3 dependents

merck

psm3mkv:Evaluate Partitioned Survival and State Transition Models

Fits and evaluates three-state partitioned survival analyses (PartSAs) and Markov models (clock forward or clock reset) to progression and overall survival data typically collected in oncology clinical trials. These model structures are typically considered in cost-effectiveness modeling in advanced/metastatic cancer indications. Muston (2024). "Informing structural assumptions for three state oncology cost-effectiveness models through model efficiency and fit". Applied Health Economics and Health Policy.

Maintained by Dominic Muston. Last updated 10 months ago.

10 stars 6.43 score 1 scripts

paternogbc

sensiPhy:Sensitivity Analysis for Comparative Methods

An implementation of sensitivity analysis for phylogenetic comparative methods. The package is an umbrella of statistical and graphical methods that estimate and report different types of uncertainty in PCM: (i) Species Sampling uncertainty (sample size; influential species and clades). (ii) Phylogenetic uncertainty (different topologies and/or branch lengths). (iii) Data uncertainty (intraspecific variation and measurement error).

Maintained by Gustavo Paterno. Last updated 5 years ago.

comparative-methods ecology evolution phylogenetics sensitivity-analysis

13 stars 6.38 score 61 scripts

trackerproject

trackeR:Infrastructure for Running, Cycling and Swimming Data from GPS-Enabled Tracking Devices

Provides infrastructure for handling running, cycling and swimming data from GPS-enabled tracking devices within R. The package provides methods to extract, clean and organise workout and competition data into session-based and unit-aware data objects of class 'trackeRdata' (S3 class). The information can then be visualised, summarised, and analysed through flexible and extensible methods. Frick and Kosmidis (2017) <doi: 10.18637/jss.v082.i07>, which is updated and maintained as one of the vignettes, provides detailed descriptions of the package and its methods, and real-data demonstrations of the package functionality.

Maintained by Ioannis Kosmidis. Last updated 1 years ago.

90 stars 6.37 score 58 scripts 1 dependents

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.

6 stars 6.33 score 30 scripts

ahgroup

DSAIDE:Dynamical Systems Approach to Infectious Disease Epidemiology (Ecology/Evolution)

Exploration of simulation models (apps) of various infectious disease transmission dynamics scenarios. The purpose of the package is to help individuals learn about infectious disease epidemiology (ecology/evolution) from a dynamical systems perspective. All apps include explanations of the underlying models and instructions on what to do with the models.

Maintained by Andreas Handel. Last updated 1 years ago.

26 stars 6.30 score 22 scripts

cvasi-tktd

cvasi:Calibration, Validation, and Simulation of TKTD Models

Eases the use of ecotoxicological effect models. Can simulate common toxicokinetic-toxicodynamic (TK/TD) models such as General Unified Threshold models of Survival (GUTS) and Lemna. It can derive effects and effect profiles (EPx) from scenarios. It supports the use of 'tidyr' workflows employing the pipe symbol. Time-consuming tasks can be parallelized.

Maintained by Nils Kehrein. Last updated 11 days ago.

ecotoxicology modeling simulation

2 stars 6.27 score 12 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 2 days ago.

4 stars 6.25 score 15 scripts 1 dependents

ahgroup

DSAIRM:Dynamical Systems Approach to Immune Response Modeling

Simulation models (apps) of various within-host immune response scenarios. The purpose of the package is to help individuals learn about within-host infection and immune response modeling from a dynamical systems perspective. All apps include explanations of the underlying models and instructions on what to do with the models.

Maintained by Andreas Handel. Last updated 8 months ago.

34 stars 6.19 score 23 scripts

frmunoz

ecolottery:Coalescent-Based Simulation of Ecological Communities

Coalescent-Based Simulation of Ecological Communities as proposed by Munoz et al. (2018) <doi:10.1111/2041-210X.12918>. The package includes a tool for estimating parameters of community assembly by using Approximate Bayesian Computation.

Maintained by François Munoz. Last updated 2 years ago.

15 stars 6.18 score 17 scripts 1 dependents

florianstijven

Surrogate:Evaluation of Surrogate Endpoints in Clinical Trials

In a clinical trial, it frequently occurs that the most credible outcome to evaluate the effectiveness of a new therapy (the true endpoint) is difficult to measure. In such a situation, it can be an effective strategy to replace the true endpoint by a (bio)marker that is easier to measure and that allows for a prediction of the treatment effect on the true endpoint (a surrogate endpoint). The package 'Surrogate' allows for an evaluation of the appropriateness of a candidate surrogate endpoint based on the meta-analytic, information-theoretic, and causal-inference frameworks. Part of this software has been developed using funding provided from the European Union's Seventh Framework Programme for research, technological development and demonstration (Grant Agreement no 602552), the Special Research Fund (BOF) of Hasselt University (BOF-number: BOF2OCPO3), GlaxoSmithKline Biologicals, Baekeland Mandaat (HBC.2022.0145), and Johnson & Johnson Innovative Medicine.

Maintained by Wim Van Der Elst. Last updated 1 months ago.

1 stars 6.15 score 133 scripts

ghuiber

BTYD:Implementing BTYD Models with the Log Sum Exp Patch

Functions for data preparation, parameter estimation, scoring, and plotting for the BG/BB (Fader, Hardie, and Shang 2010 <doi:10.1287/mksc.1100.0580>), BG/NBD (Fader, Hardie, and Lee 2005 <doi:10.1287/mksc.1040.0098>) and Pareto/NBD and Gamma/Gamma (Fader, Hardie, and Lee 2005 <doi:10.1509/jmkr.2005.42.4.415>) models.

Maintained by Gabi Huiber. Last updated 3 years ago.

7 stars 6.03 score 103 scripts 1 dependents

zhenkewu

baker:"Nested Partially Latent Class Models"

Provides functions to specify, fit and visualize nested partially-latent class models ( Wu, Deloria-Knoll, Hammitt, and Zeger (2016) <doi:10.1111/rssc.12101>; Wu, Deloria-Knoll, and Zeger (2017) <doi:10.1093/biostatistics/kxw037>; Wu and Chen (2021) <doi:10.1002/sim.8804>) for inference of population disease etiology and individual diagnosis. In the motivating Pneumonia Etiology Research for Child Health (PERCH) study, because both quantities of interest sum to one hundred percent, the PERCH scientists frequently refer to them as population etiology pie and individual etiology pie, hence the name of the package.

Maintained by Zhenke Wu. Last updated 11 months ago.

bayesian case-control latent-class-analysis jags cpp

8 stars 6.00 score 21 scripts

jameel-institute

daedalus:Model Health, Social, and Economic Costs of a Pandemic

Model the health, education, and economic costs of directly transmitted respiratory virus pandemics, under different scenarios of prior vaccine investment and reactive interventions, using the 'DAEDALUS' integrated health-economics model adapted from Haw et al. (2022) <doi.org/10.1038/s43588-022-00233-0>.

Maintained by Pratik Gupte. Last updated 1 days ago.

decision-support epidemiological-models health-economics pandemic-preparedness public-health rcpp sdg-3 cpp openmp

4 stars 5.95 score 8 scripts

rsetienne

PBD:Protracted Birth-Death Model of Diversification

Conducts maximum likelihood analysis and simulation of the protracted birth-death model of diversification. See Etienne, R.S. & J. Rosindell 2012 <doi:10.1093/sysbio/syr091>; Lambert, A., H. Morlon & R.S. Etienne 2014, <doi:10.1007/s00285-014-0767-x>; Etienne, R.S., H. Morlon & A. Lambert 2014, <doi:10.1111/evo.12433>.

Maintained by Rampal S. Etienne. Last updated 2 months ago.

2 stars 5.95 score 49 scripts

hoehna

TESS:Diversification Rate Estimation and Fast Simulation of Reconstructed Phylogenetic Trees under Tree-Wide Time-Heterogeneous Birth-Death Processes Including Mass-Extinction Events

Simulation of reconstructed phylogenetic trees under tree-wide time-heterogeneous birth-death processes and estimation of diversification parameters under the same model. Speciation and extinction rates can be any function of time and mass-extinction events at specific times can be provided. Trees can be simulated either conditioned on the number of species, the time of the process, or both. Additionally, the likelihood equations are implemented for convenience and can be used for Maximum Likelihood (ML) estimation and Bayesian inference.

Maintained by Sebastian Hoehna. Last updated 3 years ago.

cpp

2 stars 5.93 score 95 scripts 1 dependents

hankstevens

primer:Functions and Data for the Book, a Primer of Ecology with R

Functions are primarily functions for systems of ordinary differential equations, difference equations, and eigenanalysis and projection of demographic matrices; data are for examples.

Maintained by Hank Stevens. Last updated 4 years ago.

14 stars 5.92 score 118 scripts

jeswheel

panelPomp:Inference for Panel Partially Observed Markov Processes

Data analysis based on panel partially-observed Markov process (PanelPOMP) models. To implement such models, simulate them and fit them to panel data, 'panelPomp' extends some of the facilities provided for time series data by the 'pomp' package. Implemented methods include filtering (panel particle filtering) and maximum likelihood estimation (Panel Iterated Filtering) as proposed in Breto, Ionides and King (2020) "Panel Data Analysis via Mechanistic Models" <doi:10.1080/01621459.2019.1604367>.

Maintained by Jesse Wheeler. Last updated 4 months ago.

5.91 score 45 scripts

caetanods

ratematrix:Bayesian Estimation of the Evolutionary Rate Matrix

The Evolutionary Rate Matrix is a variance-covariance matrix which describes both the rates of trait evolution and the evolutionary correlation among multiple traits. This package has functions to estimate these parameters using Bayesian MCMC. It is possible to test if the pattern of evolutionary correlations among traits has changed between predictive regimes painted along the branches of the phylogenetic tree. Regimes can be created a priori or estimated as part of the MCMC under a joint estimation approach. The package has functions to run MCMC chains, plot results, evaluate convergence, and summarize posterior distributions.

Maintained by Daniel Caetano. Last updated 2 years ago.

openblas cpp openmp

10 stars 5.91 score 18 scripts 1 dependents

r-forge

mlt.docreg:Most Likely Transformations: Documentation and Regression Tests

Additional documentation, a package vignette and regression tests for package mlt.

Maintained by Torsten Hothorn. Last updated 10 days ago.

5.84 score

rsetienne

secsse:Several Examined and Concealed States-Dependent Speciation and Extinction

Simultaneously infers state-dependent diversification across two or more states of a single or multiple traits while accounting for the role of a possible concealed trait. See Herrera-Alsina et al. (2019) <doi:10.1093/sysbio/syy057>.

Maintained by Rampal S. Etienne. Last updated 11 months ago.

cpp

1 stars 5.83 score 34 scripts

profandyfield

adventr:Interactive R Tutorials to Accompany Field (2016), "An Adventure in Statistics"

Interactive 'R' tutorials written using 'learnr' for Field (2016), "An Adventure in Statistics", <ISBN:9781446210451>. Topics include general workflow in 'R' and 'Rstudio', the 'R' environment and 'tidyverse', summarizing data, model fitting, central tendency, visualising data using 'ggplot2', inferential statistics and robust estimation, hypothesis testing, the general linear model, comparing means, repeated measures designs, factorial designs, multilevel models, growth models, and generalized linear models (logistic regression).

Maintained by Andy Field. Last updated 4 years ago.

36 stars 5.79 score 34 scripts

r-lum

RLumModel:Solving Ordinary Differential Equations to Understand Luminescence

A collection of functions to simulate luminescence signals in quartz and Al2O3 based on published models.

Maintained by Johannes Friedrich. Last updated 3 years ago.

differential-equations energy-band-model geochronology luminescence luminescence-models modelling quartz simulation openblas cpp

5 stars 5.73 score 18 scripts 1 dependents

geobosh

Countr:Flexible Univariate Count Models Based on Renewal Processes

Flexible univariate count models based on renewal processes. The models may include covariates and can be specified with familiar formula syntax as in glm() and package 'flexsurv'. The methodology is described by Kharrat et all (2019) <doi:10.18637/jss.v090.i13> (included as vignette 'Countr_guide' in the package). If the suggested package 'pscl' is not available from CRAN, it can be installed with 'remotes::install_github("cran/pscl")'. It is no longer used by the functions in this package but is needed for some of the extended examples.

Maintained by Georgi N. Boshnakov. Last updated 1 years ago.

count-data renewal-process sports-modelling openblas cpp

4 stars 5.71 score 43 scripts

mrc-ide

odin.dust:Compile Odin to Dust

Less painful than it sounds, this package compiles an odin model to use dust, our new stochastic model system. Supports only a subset of odin models (discrete time stochastic models with no interpolation and no delays).

Maintained by Rich FitzJohn. Last updated 6 months ago.

3 stars 5.71 score 122 scripts

cneyens

raem:Analytic Element Modeling of Steady Single-Layer Groundwater Flow

A model of single-layer groundwater flow in steady-state under the Dupuit-Forchheimer assumption can be created by placing elements such as wells, area-sinks and line-sinks at arbitrary locations in the flow field. Output variables include hydraulic head and the discharge vector. Particle traces can be computed numerically in three dimensions. The underlying theory is described in Haitjema (1995) <doi:10.1016/B978-0-12-316550-3.X5000-4> and references therein.

Maintained by Cas Neyens. Last updated 7 months ago.

analytic-element-model groundwater groundwater-modelling hydrogeology hydrology

8 stars 5.68 score 6 scripts

markusul

SDModels:Spectrally Deconfounded Models

Screen for and analyze non-linear sparse direct effects in the presence of unobserved confounding using the spectral deconfounding techniques (Ćevid, Bühlmann, and Meinshausen (2020)<jmlr.org/papers/v21/19-545.html>, Guo, Ćevid, and Bühlmann (2022) <doi:10.1214/21-AOS2152>). These methods have been shown to be a good estimate for the true direct effect if we observe many covariates, e.g., high-dimensional settings, and we have fairly dense confounding. Even if the assumptions are violated, it seems like there is not much to lose, and the deconfounded models will, in general, estimate a function closer to the true one than classical least squares optimization. 'SDModels' provides functions SDAM() for Spectrally Deconfounded Additive Models (Scheidegger, Guo, and Bühlmann (2025) <doi:10.1145/3711116>) and SDForest() for Spectrally Deconfounded Random Forests (Ulmer, Scheidegger, and Bühlmann (2025) <doi:10.48550/arXiv.2502.03969>).

Maintained by Markus Ulmer. Last updated 19 days ago.

2 stars 5.67 score 15 scripts

nanhung

pksensi:Global Sensitivity Analysis in Physiologically Based Kinetic Modeling

Applying the global sensitivity analysis workflow to investigate the parameter uncertainty and sensitivity in physiologically based kinetic (PK) models, especially the physiologically based pharmacokinetic/toxicokinetic model with multivariate outputs. The package also provides some functions to check the convergence and sensitivity of model parameters. The workflow was first mentioned in Hsieh et al., (2018) <doi:10.3389/fphar.2018.00588>, then further refined (Hsieh et al., 2020 <doi:10.1016/j.softx.2020.100609>).

Maintained by Nan-Hung Hsieh. Last updated 4 months ago.

gnu-mcsim pharmacokinetics sensitivity sensitivity-analysis

5 stars 5.64 score 88 scripts

pik-piam

mrland:MadRaT land data package

The package provides land related data via the madrat framework.

Maintained by Jan Philipp Dietrich. Last updated 10 days ago.

5.59 score 3 scripts 4 dependents

bioc

UMI4Cats:UMI4Cats: Processing, analysis and visualization of UMI-4C chromatin contact data

UMI-4C is a technique that allows characterization of 3D chromatin interactions with a bait of interest, taking advantage of a sonication step to produce unique molecular identifiers (UMIs) that help remove duplication bias, thus allowing a better differential comparsion of chromatin interactions between conditions. This package allows processing of UMI-4C data, starting from FastQ files provided by the sequencing facility. It provides two statistical methods for detecting differential contacts and includes a visualization function to plot integrated information from a UMI-4C assay.

Maintained by Mireia Ramos-Rodriguez. Last updated 5 months ago.

qualitycontrol preprocessing alignment normalization visualization sequencing coverage chromatin chromatin-interaction genomics umi4c

5 stars 5.57 score 7 scripts

arnaldpuy

sensobol:Computation of Variance-Based Sensitivity Indices

It allows to rapidly compute, bootstrap and plot up to fourth-order Sobol'-based sensitivity indices using several state-of-the-art first and total-order estimators. Sobol' indices can be computed either for models that yield a scalar as a model output or for systems of differential equations. The package also provides a suit of benchmark tests functions and several options to obtain publication-ready figures of the model output uncertainty and sensitivity-related analysis. An overview of the package can be found in Puy et al. (2022) <doi:10.18637/jss.v102.i05>.

Maintained by Arnald Puy. Last updated 1 years ago.

cpp

15 stars 5.57 score 50 scripts

ropensci

agroclimatico:Índices y Estadísticos Climáticos e Hidrológicos

Conjunto de funciones para calcular índices y estadísticos climáticos hidrológicos a partir de datos tidy. Incluye una función para graficar resultados georeferenciados y e información cartográfica.

Maintained by Paola Corrales. Last updated 2 months ago.

agricultura meteorologia cpp

19 stars 5.53 score 7 scripts

dkneis

rodeo:A Code Generator for ODE-Based Models

Provides an R6 class and several utility methods to facilitate the implementation of models based on ordinary differential equations. The heart of the package is a code generator that creates compiled 'Fortran' (or 'R') code which can be passed to a numerical solver. There is direct support for solvers contained in packages 'deSolve' and 'rootSolve'.

Maintained by David Kneis. Last updated 4 months ago.

7 stars 5.53 score 24 scripts

mponce0

covid19.analytics:Load and Analyze Live Data from the COVID-19 Pandemic

Load and analyze updated time series worldwide data of reported cases for the Novel Coronavirus Disease (COVID-19) from different sources, including the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE) data repository <https://github.com/CSSEGISandData/COVID-19>, "Our World in Data" <https://github.com/owid/> among several others. The datasets reporting the COVID-19 cases are available in two main modalities, as a time series sequences and aggregated data for the last day with greater spatial resolution. Several analysis, visualization and modelling functions are available in the package that will allow the user to compute and visualize total number of cases, total number of changes and growth rate globally or for an specific geographical location, while at the same time generating models using these trends; generate interactive visualizations and generate Susceptible-Infected-Recovered (SIR) model for the disease spread.

Maintained by Marcelo Ponce. Last updated 3 years ago.

covid19 covid19-data ncov2019 sars-cov-2

33 stars 5.52 score 20 scripts

japhir

snvecR:Calculate Earth’s Obliquity and Precession in the Past

Easily calculate precession and obliquity from an orbital solution (defaults to ZB18a from Zeebe and Lourens (2019) <doi:10.1126/science.aax0612>) and assumed or reconstructed values for dynamical ellipticity (Ed) and tidal dissipation (Td). This is a translation and adaptation of the 'C'-code in the supplementary material to Zeebe and Lourens (2022) <doi:10.1029/2021PA004349>, with further details on the methodology described in Zeebe (2022) <doi:10.3847/1538-3881/ac80f8>. The name of the 'C'-routine is 'snvec', which refers to the key units of computation: spin vector s and orbit normal vector n.

Maintained by Ilja Kocken. Last updated 20 days ago.

4 stars 5.51 score 4 scripts

gabrielnakamura

FishPhyloMaker:Phylogenies for a List of Finned-Ray Fishes

Provides an alternative to facilitate the construction of a phylogeny for fish species from a list of species or a community matrix using as a backbone the phylogenetic tree proposed by Rabosky et al. (2018) <doi:10.1038/s41586-018-0273-1>.

Maintained by Gabriel Nakamura. Last updated 1 years ago.

8 stars 5.49 score 13 scripts

shabbychef

sadists:Some Additional Distributions

Provides the density, distribution, quantile and generation functions of some obscure probability distributions, including the doubly non-central t, F, Beta, and Eta distributions; the lambda-prime and K-prime; the upsilon distribution; the (weighted) sum of non-central chi-squares to a power; the (weighted) sum of log non-central chi-squares; the product of non-central chi-squares to powers; the product of doubly non-central F variables; the product of independent normals.

Maintained by Steven E. Pav. Last updated 4 years ago.

8 stars 5.48 score 25 scripts 1 dependents

surmann

ODEsensitivity:Sensitivity Analysis of Ordinary Differential Equations

Performs sensitivity analysis in ordinary differential equation (ode) models. The package utilize the ode interface from 'deSolve' and connects it with the sensitivity analysis from 'sensitivity'. Additionally we add a method to run the sensitivity analysis on variables with class 'ODEnetwork'. A detailed plotting function provides outputs on the calculations. The method is described by Weber, Theers, Surmann, Ligges, and Weihs (2018) <doi:10.17877/DE290R-18874>.

Maintained by Dirk Surmann. Last updated 6 years ago.

6 stars 5.47 score 49 scripts

alvesks

epifitter:Analysis and Simulation of Plant Disease Progress Curves

Analysis and visualization of plant disease progress curve data. Functions for fitting two-parameter population dynamics models (exponential, monomolecular, logistic and Gompertz) to proportion data for single or multiple epidemics using either linear or no-linear regression. Statistical and visual outputs are provided to aid in model selection. Synthetic curves can be simulated for any of the models given the parameters. See Laurence V. Madden, Gareth Hughes, and Frank van den Bosch (2007) <doi:10.1094/9780890545058> for further information on the methods.

Maintained by Kaique dos S. Alves. Last updated 2 months ago.

5 stars 5.42 score 53 scripts

matteo21q

dani:Design and Analysis of Non-Inferiority Trials

Provides tools to help with the design and analysis of non-inferiority trials. These include functions for doing sample size calculations and for analysing non-inferiority trials, using a variety of outcome types and population-level sumamry measures. It also features functions to make trials more resilient by using the concept of non-inferiority frontiers, as described in Quartagno et al. (2019) <arXiv:1905.00241>. Finally it includes function to design and analyse MAMS-ROCI (aka DURATIONS) trials.

Maintained by Matteo Quartagno. Last updated 7 months ago.

2 stars 5.33 score 27 scripts

rcalinjageman

esci:Estimation Statistics with Confidence Intervals

A collection of functions and 'jamovi' module for the estimation approach to inferential statistics, the approach which emphasizes effect sizes, interval estimates, and meta-analysis. Nearly all functions are based on 'statpsych' and 'metafor'. This package is still under active development, and breaking changes are likely, especially with the plot and hypothesis test functions. Data sets are included for all examples from Cumming & Calin-Jageman (2024) <ISBN:9780367531508>.

Maintained by Robert Calin-Jageman. Last updated 1 months ago.

jamovi jasp science statistics visualization

24 stars 5.24 score 12 scripts

alexanderlynl

safestats:Safe Anytime-Valid Inference

Functions to design and apply tests that are anytime valid. The functions can be used to design hypothesis tests in the prospective/randomised control trial setting or in the observational/retrospective setting. The resulting tests remain valid under both optional stopping and optional continuation. The current version includes safe t-tests and safe tests of two proportions. For details on the theory of safe tests, see Grunwald, de Heide and Koolen (2019) "Safe Testing" <arXiv:1906.07801>, for details on safe logrank tests see ter Schure, Perez-Ortiz, Ly and Grunwald (2020) "The Safe Logrank Test: Error Control under Continuous Monitoring with Unlimited Horizon" <arXiv:2011.06931v3> and Turner, Ly and Grunwald (2021) "Safe Tests and Always-Valid Confidence Intervals for contingency tables and beyond" <arXiv:2106.02693> for details on safe contingency table tests.

Maintained by Alexander Ly. Last updated 2 years ago.

evalues hacktoberfest safe-testing statistics

6 stars 5.23 score 14 scripts

bioc

spatialFDA:A Tool for Spatial Multi-sample Comparisons

spatialFDA is a package to calculate spatial statistics metrics. The package takes a SpatialExperiment object and calculates spatial statistics metrics using the package spatstat. Then it compares the resulting functions across samples/conditions using functional additive models as implemented in the package refund. Furthermore, it provides exploratory visualisations using functional principal component analysis, as well implemented in refund.

Maintained by Martin Emons. Last updated 1 months ago.

software spatial transcriptomics

3 stars 5.18 score 6 scripts

phillipbvetter

ctsmTMB:Continuous Time Stochastic Modelling using Template Model Builder

ctsmTMB is an R package for parameter and state estimation and forecasting in stochastic state space systems. These are partially observed state space systems that whose latent states evolve according to a system of stochastic differential equation. The package employs the R6 object oriented class for user-friendly model construction, and uses the TMB/RTMB packages for algorithmic differentiation and Laplace approximation. The estimation methods implemented are variations of Kalman Filters, in addition to a filtering scheme based on the Laplace approximation.

Maintained by Phillip Brinck Vetter. Last updated 10 days ago.

cpp

2 stars 5.13 score

ropensci

treedata.table:Manipulation of Matched Phylogenies and Data using 'data.table'

An implementation that combines trait data and a phylogenetic tree (or trees) into a single object of class treedata.table. The resulting object can be easily manipulated to simultaneously change the trait- and tree-level sampling. Currently implemented functions allow users to use a 'data.table' syntax when performing operations on the trait dataset within the treedata.table object.

Maintained by Cristian Roman-Palacios. Last updated 4 years ago.

7 stars 5.12 score 25 scripts

pik-piam

mrmagpie:madrat based MAgPIE Input Data Library

Provides functions for MAgPIE country and cellular input data generation.

Maintained by Kristine Karstens. Last updated 11 days ago.

5.12 score 2 dependents

antoniofabio

tseriesChaos:Analysis of Nonlinear Time Series

Routines for the analysis of nonlinear time series. This work is largely inspired by the TISEAN project, by Rainer Hegger, Holger Kantz and Thomas Schreiber: <http://www.mpipks-dresden.mpg.de/~tisean/>.

Maintained by Antonio Fabio Di Narzo. Last updated 6 years ago.

3 stars 5.12 score 106 scripts 6 dependents

pik-piam

mrlandcore:One-line description of this awesome package

One-paragraph description of this awesome package.

Maintained by Felicitas Beier. Last updated 2 months ago.

1 stars 5.11 score 16 dependents

kaskr

RTMBode:Solving ODEs with 'deSolve' and 'RTMB'.

Solve ODEs as part of 'RTMB' objective functions with algorithmic derivatives to any order. ODE adjoint code is obtained via 'RTMB' using automatic variable augmentation of the system equation.

Maintained by kaskr. Last updated 2 months ago.

54 stars 5.11 score 1 scripts

julia-wrobel

mxfda:A Functional Data Analysis Package for Spatial Single Cell Data

Methods and tools for deriving spatial summary functions from single-cell imaging data and performing functional data analyses. Functions can be applied to other single-cell technologies such as spatial transcriptomics. Functional regression and functional principal component analysis methods are in the 'refund' package <https://cran.r-project.org/package=refund> while calculation of the spatial summary functions are from the 'spatstat' package <https://spatstat.org/>.

Maintained by Alex Soupir. Last updated 1 months ago.

1 stars 5.08 score 8 scripts

surmann

ODEnetwork:Network of Differential Equations

Simulates a network of ordinary differential equations of order two. The package provides an easy interface to construct networks. In addition you are able to define different external triggers to manipulate the trajectory. The method is described by Surmann, Ligges, and Weihs (2014) <doi:10.1109/ENERGYCON.2014.6850482>.

Maintained by Dirk Surmann. Last updated 5 years ago.

4 stars 5.08 score 20 scripts 1 dependents

parksw3

fitode:Tools for Ordinary Differential Equations Model Fitting

Methods and functions for fitting ordinary differential equations (ODE) model in 'R'. Sensitivity equations are used to compute the gradients of ODE trajectories with respect to underlying parameters, which in turn allows for more stable fitting. Other fitting methods, such as MCMC (Markov chain Monte Carlo), are also available.

Maintained by Sang Woo Park. Last updated 1 months ago.

6 stars 5.01 score 34 scripts

kaifenglu

eventPred:Event Prediction

Predicts enrollment and events at the design or analysis stage using specified enrollment and time-to-event models through simulations.

Maintained by Kaifeng Lu. Last updated 9 days ago.

1 stars 4.95 score 20 scripts 1 dependents

bgoussen

BeeGUTS:General Unified Threshold Model of Survival for Bees using Bayesian Inference

Tools to calibrate, validate, and make predictions with the General Unified Threshold model of Survival adapted for Bee species. The model is presented in the publication from Baas, J., Goussen, B., Miles, M., Preuss, T.G., Roessing, I. (2022) <doi:10.1002/etc.5423> and Baas, J., Goussen, B., Taenzler, V., Roeben, V., Miles, M., Preuss, T.G., van den Berg, S., Roessink, I. (2024) <doi:10.1002/etc.5871>, and is based on the GUTS framework Jager, T., Albert, C., Preuss, T.G. and Ashauer, R. (2011) <doi:10.1021/es103092a>. The authors are grateful to Bayer A.G. for its financial support.

Maintained by Benoit Goussen. Last updated 5 months ago.

cpp

3 stars 4.95 score 6 scripts

refunders

refund.shiny:Interactive Plotting for Functional Data Analyses

Produces Shiny applications for different types of popular functional data analyses. The functional data analyses are implemented in the refund package, then refund.shiny reads in the refund object and implements an object-specific set of plots based on the object class using S3.

Maintained by Julia Wrobel. Last updated 1 years ago.

4 stars 4.91 score 45 scripts

pik-piam

mrtransport:Input data generation for the EDGE-Transport model

The mrtransport package contains data preprocessing for the EDGE-Transport model.

Maintained by Johanna Hoppe. Last updated 1 days ago.

4.86 score 3 dependents

dusty-turner

ggvfields:Vector Field Visualizations with 'ggplot2'

A 'ggplot2' extension for visualizing vector fields in two-dimensional space. Provides flexible tools for creating vector and stream field layers, visualizing gradients and potential fields, and smoothing vector and scalar data to estimate underlying patterns.

Maintained by Dusty Turner. Last updated 1 days ago.

4 stars 4.86 score

noeliaof

SEI:Calculating Standardised Indices

Convert a time series of observations to a time series of standardised indices that can be used to monitor variables on a common and probabilistically interpretable scale. The indices can be aggregated and rescaled to different time scales, visualised using plot capabilities, and calculated using a range of distributions. This includes flexible non-parametric and non-stationary methods.

Maintained by Sam Allen. Last updated 8 months ago.

3 stars 4.86 score 12 scripts

sebdejean

CCA:Canonical Correlation Analysis

Provides a set of functions that extend the 'cancor' function with new numerical and graphical outputs. It also include a regularized extension of the canonical correlation analysis to deal with datasets with more variables than observations.

Maintained by Sébastien Déjean. Last updated 2 years ago.

4.85 score 334 scripts 3 dependents

pik-piam

mrvalidation:madrat data preparation for validation purposes

Package contains routines to prepare data for validation exercises.

Maintained by Benjamin Leon Bodirsky. Last updated 6 days ago.

4.81 score 9 scripts 1 dependents

glotaran

TIMP:Fitting Separable Nonlinear Models in Spectroscopy and Microscopy

A problem solving environment (PSE) for fitting separable nonlinear models to measurements arising in physics and chemistry experiments, as described by Mullen & van Stokkum (2007) <doi:10.18637/jss.v018.i03> for its use in fitting time resolved spectroscopy data, and as described by Laptenok et al. (2007) <doi:10.18637/jss.v018.i08> for its use in fitting Fluorescence Lifetime Imaging Microscopy (FLIM) data, in the study of Förster Resonance Energy Transfer (FRET). `TIMP` also serves as the computation backend for the `GloTarAn` software, a graphical user interface for the package, as described in Snellenburg et al. (2012) <doi:10.18637/jss.v049.i03>.

Maintained by Joris Snellenburg. Last updated 2 years ago.

parameter-estimation

3 stars 4.80 score 14 scripts 1 dependents

jlilienthal

TLMoments:Calculate TL-Moments and Convert Them to Distribution Parameters

Calculates empirical TL-moments (trimmed L-moments) of arbitrary order and trimming, and converts them to distribution parameters.

Maintained by Jona Lilienthal. Last updated 3 years ago.

cpp

4.79 score 29 scripts 22 dependents

dfrancom

BASS:Bayesian Adaptive Spline Surfaces

Bayesian fitting and sensitivity analysis methods for adaptive spline surfaces described in <doi:10.18637/jss.v094.i08>. Built to handle continuous and categorical inputs as well as functional or scalar output. An extension of the methodology in Denison, Mallick and Smith (1998) <doi:10.1023/A:1008824606259>.

Maintained by Devin Francom. Last updated 2 years ago.

1 stars 4.78 score 173 scripts

tpetzoldt

simecol:Simulation of Ecological (and Other) Dynamic Systems

An object oriented framework to simulate ecological (and other) dynamic systems. It can be used for differential equations, individual-based (or agent-based) and other models as well. It supports structuring of simulation scenarios (to avoid copy and paste) and aims to improve readability and re-usability of code.

Maintained by Thomas Petzoldt. Last updated 8 months ago.

4.76 score 190 scripts

jatanrt

eprscope:Processing and Analysis of Electron Paramagnetic Resonance Data and Spectra in Chemistry

Processing, analysis and plottting of Electron Paramagnetic Resonance (EPR) spectra in chemistry. Even though the package is mainly focused on continuous wave (CW) EPR/ENDOR, many functions may be also used for the integrated forms of 1D PULSED EPR spectra. It is able to find the most important spectral characteristics like g-factor, linewidth, maximum of derivative or integral intensities and single/double integrals. This is especially important in spectral (time) series consisting of many EPR spectra like during variable temperature experiments, electrochemical or photochemical radical generation and/or decay. Package also enables processing of data/spectra for the analytical (quantitative) purposes. Namely, how many radicals or paramagnetic centers can be found in the analyte/sample. The goal is to evaluate rate constants, considering different kinetic models, to describe the radical reactions. The key feature of the package resides in processing of the universal ASCII text formats (such as '.txt', '.csv' or '.asc') from scratch. No proprietary formats are used (except the MATLAB EasySpin outputs) and in such respect the package is in accordance with the FAIR data principles. Upon 'reading' (also providing automatic procedures for the most common EPR spectrometers) the spectral data are transformed into the universal R 'data frame' format. Subsequently, the EPR spectra can be visualized and are fully consistent either with the 'ggplot2' package or with the interactive formats based on 'plotly'. Additionally, simulations and fitting of the isotropic EPR spectra are also included in the package. Advanced simulation parameters provided by the MATLAB-EasySpin toolbox and results from the quantum chemical calculations like g-factor and hyperfine splitting/coupling constants (a/A) can be compared and summarized in table-format in order to analyze the EPR spectra by the most effective way.

Maintained by Ján Tarábek. Last updated 2 days ago.

chemistry data-analysis data-visualization epr esr fitting optimization programming-language reproducible-research scientific-plotting spectroscopy openjdk

4.76 score 7 scripts

egarpor

goffda:Goodness-of-Fit Tests for Functional Data

Implementation of several goodness-of-fit tests for functional data. Currently, mostly related with the functional linear model with functional/scalar response and functional/scalar predictor. The package allows for the replication of the data applications considered in García-Portugués, Álvarez-Liébana, Álvarez-Pérez and González-Manteiga (2021) <doi:10.1111/sjos.12486>.

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

functional-data-analysis goodness-of-fit reproducible-research statistics openblas cpp

10 stars 4.76 score 19 scripts 1 dependents

ropensci

phruta:Phylogenetic Reconstruction and Time-dating

The phruta R package is designed to simplify the basic phylogenetic pipeline. Specifically, all code is run within the same program and data from intermediate steps are saved in independent folders. Furthermore, all code is run within the same environment which increases the reproducibility of your analysis. phruta retrieves gene sequences, combines newly downloaded and local gene sequences, and performs sequence alignments.

Maintained by Cristian Roman Palacios. Last updated 9 months ago.

9 stars 4.75 score 14 scripts

rafael-ayala

asteRisk:Computation of Satellite Position

Provides basic functionalities to calculate the position of satellites given a known state vector. The package includes implementations of the SGP4 and SDP4 simplified perturbation models to propagate orbital state vectors, as well as utilities to read TLE files and convert coordinates between different frames of reference. Several of the functionalities of the package (including the high-precision numerical orbit propagator) require the coefficients and data included in the 'asteRiskData' package, available in a 'drat' repository. To install this data package, run 'install.packages("asteRiskData", repos="https://rafael-ayala.github.io/drat/")'. Felix R. Hoots, Ronald L. Roehrich and T.S. Kelso (1988) <https://celestrak.org/NORAD/documentation/spacetrk.pdf>. David Vallado, Paul Crawford, Richard Hujsak and T.S. Kelso (2012) <doi:10.2514/6.2006-6753>. Felix R. Hoots, Paul W. Schumacher Jr. and Robert A. Glover (2014) <doi:10.2514/1.9161>.

Maintained by Rafael Ayala. Last updated 11 months ago.

cpp

6 stars 4.74 score 23 scripts

bioc

SBMLR:SBML-R Interface and Analysis Tools

This package contains a systems biology markup language (SBML) interface to R.

Maintained by Tomas Radivoyevitch. Last updated 5 months ago.

graphandnetwork pathways network

4.73 score 45 scripts

chedgala

MomTrunc:Moments of Folded and Doubly Truncated Multivariate Distributions

It computes arbitrary products moments (mean vector and variance-covariance matrix), for some double truncated (and folded) multivariate distributions. These distributions belong to the family of selection elliptical distributions, which includes well known skewed distributions as the unified skew-t distribution (SUT) and its particular cases as the extended skew-t (EST), skew-t (ST) and the symmetric student-t (T) distribution. Analogous normal cases unified skew-normal (SUN), extended skew-normal (ESN), skew-normal (SN), and symmetric normal (N) are also included. Density, probabilities and random deviates are also offered for these members.

Maintained by Christian E. Galarza. Last updated 5 months ago.

generation-algorithms moments probability-statistics openblas cpp

4.73 score 17 scripts 7 dependents

mflores72000

qcr:Quality Control Review

Univariate and multivariate SQC tools that completes and increases the SQC techniques available in R. Apart from integrating different R packages devoted to SQC ('qcc','MSQC'), provides nonparametric tools that are highly useful when Gaussian assumption is not met. This package computes standard univariate control charts for individual measurements, X-bar, S, R, p, np, c, u, EWMA and CUSUM. In addition, it includes functions to perform multivariate control charts such as Hotelling T2, MEWMA and MCUSUM. As representative feature, multivariate nonparametric alternatives based on data depth are implemented in this package: r, Q and S control charts. In addition, Phase I and II control charts for functional data are included. This package also allows the estimation of the most complete set of capability indices from first to fourth generation, covering the nonparametric alternatives, and performing the corresponding capability analysis graphical outputs, including the process capability plots.

Maintained by Miguel Flores. Last updated 2 years ago.

4.71 score 172 scripts 1 dependents

pedscience

clinicalsignificance:A Toolbox for Clinical Significance Analyses in Intervention Studies

A clinical significance analysis can be used to determine if an intervention has a meaningful or practical effect for patients. You provide a tidy data set plus a few more metrics and this package will take care of it to make your results publication ready. Accompanying package to Claus et al. <doi:10.18637/jss.v111.i01>.

Maintained by Benedikt Claus. Last updated 4 months ago.

1 stars 4.70 score 20 scripts

tguillerme

treats:Trees and Traits Simulations

A modular package for simulating phylogenetic trees and species traits jointly. Trees can be simulated using modular birth-death parameters (e.g. changing starting parameters or algorithm rules). Traits can be simulated in any way designed by the user. The growth of the tree and the traits can influence each other through modifiers objects providing rules for affecting each other. Finally, events can be created to modify both the tree and the traits under specific conditions ( Guillerme, 2024 <DOI:10.1111/2041-210X.14306>).

Maintained by Thomas Guillerme. Last updated 2 days ago.

3 stars 4.69 score 19 scripts

trackerproject

trackeRapp:Interface for the Analysis of Running, Cycling and Swimming Data from GPS-Enabled Tracking Devices

Provides an integrated user interface and workflow for the analysis of running, cycling and swimming data from GPS-enabled tracking devices through the 'trackeR' <https://CRAN.R-project.org/package=trackeR> R package.

Maintained by Ioannis Kosmidis. Last updated 3 years ago.

data-visualization shiny sports-app web-app web-development

32 stars 4.68 score 2 scripts

pik-piam

mrfactors:MADRaT based package on factor inputs

This package provides functions for MAgPIE input data on factor inputs to agricultural production (with a focus on capital and labor).

Maintained by Debbora Leip. Last updated 3 days ago.

4.67 score 1 scripts 5 dependents

mpt-network

MPTmultiverse:Multiverse Analysis of Multinomial Processing Tree Models

Statistical or cognitive modeling usually requires a number of more or less arbitrary choices creating one specific path through a 'garden of forking paths'. The multiverse approach (Steegen, Tuerlinckx, Gelman, & Vanpaemel, 2016, <doi:10.1177/1745691616658637>) offers a principled alternative in which results for all possible combinations of reasonable modeling choices are reported. MPTmultiverse performs a multiverse analysis for multinomial processing tree (MPT, Riefer & Batchelder, 1988, <doi:10.1037/0033-295X.95.3.318>) models combining maximum-likelihood/frequentist and Bayesian estimation approaches with different levels of pooling (i.e., data aggregation). For the frequentist approaches, no pooling (with and without parametric or nonparametric bootstrap) and complete pooling are implemented using MPTinR <https://cran.r-project.org/package=MPTinR>. For the Bayesian approaches, no pooling, complete pooling, and three different variants of partial pooling are implemented using TreeBUGS <https://cran.r-project.org/package=TreeBUGS>. The main function is fit_mpt() who performs the multiverse analysis in one call.

Maintained by Henrik Singmann. Last updated 2 years ago.

jags cpp

3 stars 4.65 score 3 scripts

cran

ftsa:Functional Time Series Analysis

Functions for visualizing, modeling, forecasting and hypothesis testing of functional time series.

Maintained by Han Lin Shang. Last updated 1 months ago.

6 stars 4.61 score 10 dependents

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

4 stars 4.60 score 3 scripts

cboettig

pmc:Phylogenetic Monte Carlo

Monte Carlo based model choice for applied phylogenetics of continuous traits. Method described in Carl Boettiger, Graham Coop, Peter Ralph (2012) Is your phylogeny informative? Measuring the power of comparative methods, Evolution 66 (7) 2240-51. <doi:10.1111/j.1558-5646.2011.01574.x>.

Maintained by Carl Boettiger. Last updated 1 years ago.

2 stars 4.60 score 10 scripts

maple-health-group

easysurv:Simplify Survival Data Analysis and Model Fitting

Inspect survival data, plot Kaplan-Meier curves, assess the proportional hazards assumption, fit parametric survival models, predict and plot survival and hazards, and export the outputs to 'Excel'. A simple interface for fitting survival models using flexsurv::flexsurvreg(), flexsurv::flexsurvspline(), flexsurvcure::flexsurvcure(), and survival::survreg().

Maintained by Niall Davison. Last updated 9 months ago.

4 stars 4.60 score 7 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

4.60 score 4 scripts

lukasklima

quid:Bayesian Mixed Models for Qualitative Individual Differences

Test whether equality and order constraints hold for all individuals simultaneously by comparing Bayesian mixed models through Bayes factors. A tutorial style vignette and a quickstart guide are available, via vignette("manual", "quid"), and vignette("quickstart", "quid") respectively. See Haaf and Rouder (2017) <doi:10.1037/met0000156>; Haaf, Klaassen and Rouder (2019) <doi:10.31234/osf.io/a4xu9>; and Rouder & Haaf (2021) <doi:10.5334/joc.131>.

Maintained by Lukas Klima. Last updated 3 years ago.

3 stars 4.59 score 13 scripts

hpetren

chemodiv:Analysing Chemodiversity of Phytochemical Data

Quantify and visualise various measures of chemical diversity and dissimilarity, for phytochemical compounds and other sets of chemical composition data. Importantly, these measures can incorporate biosynthetic and/or structural properties of the chemical compounds, resulting in a more comprehensive quantification of diversity and dissimilarity. For details, see Petrén, Köllner and Junker (2023) <doi:10.1111/nph.18685>.

Maintained by Hampus Petrén. Last updated 2 years ago.

5 stars 4.57 score 15 scripts

karlines

ReacTran:Reactive Transport Modelling in 1d, 2d and 3d

Routines for developing models that describe reaction and advective-diffusive transport in one, two or three dimensions. Includes transport routines in porous media, in estuaries, and in bodies with variable shape.

Maintained by Karline Soetaert. Last updated 8 years ago.

fortran

6 stars 4.57 score 52 scripts

mrc-ide

gonovax:Deterministic Compartmental Model of Gonorrhoea with Vaccination

Model for gonorrhoea vaccination, using odin.

Maintained by Lilith Whittles. Last updated 16 days ago.

3 stars 4.56 score

chjackson

disbayes:Bayesian Multi-State Modelling of Chronic Disease Burden Data

Estimation of incidence and case fatality for a chronic disease, given partial information, using a multi-state model. Given data on age-specific mortality and either incidence or prevalence, Bayesian inference is used to estimate the posterior distributions of incidence, case fatality, and functions of these such as prevalence. The methods are described in Jackson et al. (2023) <doi:10.1093/jrsssa/qnac015>.

Maintained by Christopher Jackson. Last updated 1 years ago.

cpp

7 stars 4.54 score 10 scripts

colemanrharris

mxnorm:Apply Normalization Methods to Multiplexed Images

Implements methods to normalize multiplexed imaging data, including statistical metrics and visualizations to quantify technical variation in this data type. Reference for methods listed here: Harris, C., Wrobel, J., & Vandekar, S. (2022). mxnorm: An R Package to Normalize Multiplexed Imaging Data. Journal of Open Source Software, 7(71), 4180, <doi:10.21105/joss.04180>.

Maintained by Coleman Harris. Last updated 2 years ago.

7 stars 4.54 score 7 scripts

ricgbl

etree:Classification and Regression with Structured and Mixed-Type Data

Implementation of Energy Trees, a statistical model to perform classification and regression with structured and mixed-type data. The model has a similar structure to Conditional Trees, but brings in Energy Statistics to test independence between variables that are possibly structured and of different nature. Currently, the package covers functions and graphs as structured covariates. It builds upon 'partykit' to provide functionalities for fitting, printing, plotting, and predicting with Energy Trees. Energy Trees are described in Giubilei et al. (2022) <arXiv:2207.04430>.

Maintained by Riccardo Giubilei. Last updated 3 years ago.

3 stars 4.52 score 11 scripts

alex-haixuw

pCODE:Estimation of an Ordinary Differential Equation Model by Parameter Cascade Method

An implementation of the parameter cascade method Ramsay, J. O., Hooker,G., Campbell, D., and Cao, J. (2007) <doi:10.1111/j.1467-9868.2007.00610.x> for estimating ordinary differential equation models with missing or complete observations. It combines smoothing method and profile estimation to estimate any non-linear dynamic system. The package also offers variance estimates for parameters of interest based on either bootstrap or Delta method.

Maintained by Haixu Wang. Last updated 3 years ago.

3 stars 4.48 score 6 scripts

dcourvoisier

doremi:Dynamics of Return to Equilibrium During Multiple Inputs

Provides models to fit the dynamics of a regulated system experiencing exogenous inputs. The underlying models use differential equations and linear mixed-effects regressions to estimate the coefficients of the equation. With them, the functions can provide an estimated signal. The package provides simulation and analysis functions and also print, summary, plot and predict methods, adapted to the function outputs, for easy implementation and presentation of results.

Maintained by Mongin Denis. Last updated 3 years ago.

4.48 score 25 scripts 1 dependents

kelliejarcher

hdcuremodels:Penalized Mixture Cure Models for High-Dimensional Data

Provides functions for fitting various penalized parametric and semi-parametric mixture cure models with different penalty functions, testing for a significant cure fraction, and testing for sufficient follow-up as described in Fu et al (2022)<doi:10.1002/sim.9513> and Archer et al (2024)<doi:10.1186/s13045-024-01553-6>. False discovery rate controlled variable selection is provided using model-X knock-offs.

Maintained by Kellie J. Archer. Last updated 8 days ago.

4.48 score 5 scripts

r-forge

stops:Structure Optimized Proximity Scaling

Methods that use flexible variants of multidimensional scaling (MDS) which incorporate parametric nonlinear distance transformations and trade-off the goodness-of-fit fit with structure considerations to find optimal hyperparameters, also known as structure optimized proximity scaling (STOPS) (Rusch, Mair & Hornik, 2023,<doi:10.1007/s11222-022-10197-w>). The package contains various functions, wrappers, methods and classes for fitting, plotting and displaying different 1-way MDS models with ratio, interval, ordinal optimal scaling in a STOPS framework. These cover essentially the functionality of the package smacofx, including Torgerson (classical) scaling with power transformations of dissimilarities, SMACOF MDS with powers of dissimilarities, Sammon mapping with powers of dissimilarities, elastic scaling with powers of dissimilarities, spherical SMACOF with powers of dissimilarities, (ALSCAL) s-stress MDS with powers of dissimilarities, r-stress MDS, MDS with powers of dissimilarities and configuration distances, elastic scaling powers of dissimilarities and configuration distances, Sammon mapping powers of dissimilarities and configuration distances, power stress MDS (POST-MDS), approximate power stress, Box-Cox MDS, local MDS, Isomap, curvilinear component analysis (CLCA), curvilinear distance analysis (CLDA) and sparsified (power) multidimensional scaling and (power) multidimensional distance analysis (experimental models from smacofx influenced by CLCA). All of these models can also be fit by optimizing over hyperparameters based on goodness-of-fit fit only (i.e., no structure considerations). The package further contains functions for optimization, specifically the adaptive Luus-Jaakola algorithm and a wrapper for Bayesian optimization with treed Gaussian process with jumps to linear models, and functions for various c-structuredness indices.

Maintained by Thomas Rusch. Last updated 3 months ago.

openjdk

1 stars 4.48 score 23 scripts

amalan-constat

fitODBOD:Modeling Over Dispersed Binomial Outcome Data Using BMD and ABD

Contains Probability Mass Functions, Cumulative Mass Functions, Negative Log Likelihood value, parameter estimation and modeling data using Binomial Mixture Distributions (BMD) (Manoj et al (2013) <doi:10.5539/ijsp.v2n2p24>) and Alternate Binomial Distributions (ABD) (Paul (1985) <doi:10.1080/03610928508828990>), also Journal article to use the package(<doi:10.21105/joss.01505>).

Maintained by Amalan Mahendran. Last updated 4 months ago.

binomial-outcome-data overdispersion

1 stars 4.44 score 139 scripts

jrvanderdoes

funkycells:Functional Data Analysis for Multiplexed Cell Images

Compare variables of interest between (potentially large numbers of) spatial interactions and meta-variables. Spatial variables are summarized using K, or other, functions, and projected for use in a modified random forest model. The model allows comparison of functional and non-functional variables to each other and to noise, giving statistical significance to the results. Included are preparation, modeling, and interpreting tools along with example datasets, as described in VanderDoes et al., (2023) <doi:10.1101/2023.07.18.549619>.

Maintained by Jeremy VanderDoes. Last updated 2 years ago.

1 stars 4.44 score 11 scripts

fernandalschumacher

skewlmm:Scale Mixture of Skew-Normal Linear Mixed Models

It fits scale mixture of skew-normal linear mixed models using either an expectation–maximization (EM) type algorithm or its accelerated version (Damped Anderson Acceleration with Epsilon Monotonicity, DAAREM), including some possibilities for modeling the within-subject dependence. Details can be found in Schumacher, Lachos and Matos (2021) <doi:10.1002/sim.8870>.

Maintained by Fernanda L. Schumacher. Last updated 2 months ago.

6 stars 4.43 score 10 scripts

weiguonimh

mMARCH.AC:Processing of Accelerometry Data with 'GGIR' in mMARCH

Mobile Motor Activity Research Consortium for Health (mMARCH) is a collaborative network of studies of clinical and community samples that employ common clinical, biological, and digital mobile measures across involved studies. One of the main scientific goals of mMARCH sites is developing a better understanding of the inter-relationships between accelerometry-measured physical activity (PA), sleep (SL), and circadian rhythmicity (CR) and mental and physical health in children, adolescents, and adults. Currently, there is no consensus on a standard procedure for a data processing pipeline of raw accelerometry data, and few open-source tools to facilitate their development. The R package 'GGIR' is the most prominent open-source software package that offers great functionality and tremendous user flexibility to process raw accelerometry data. However, even with 'GGIR', processing done in a harmonized and reproducible fashion requires a non-trivial amount of expertise combined with a careful implementation. In addition, novel accelerometry-derived features of PA/SL/CR capturing multiscale, time-series, functional, distributional and other complimentary aspects of accelerometry data being constantly proposed and become available via non-GGIR R implementations. To address these issues, mMARCH developed a streamlined harmonized and reproducible pipeline for loading and cleaning raw accelerometry data, extracting features available through 'GGIR' as well as through non-GGIR R packages, implementing several data and feature quality checks, merging all features of PA/SL/CR together, and performing multiple analyses including Joint Individual Variation Explained (JIVE), an unsupervised machine learning dimension reduction technique that identifies latent factors capturing joint across and individual to each of three domains of PA/SL/CR. In detail, the pipeline generates all necessary R/Rmd/shell files for data processing after running 'GGIR' (v2.4.0) for accelerometer data. In module 1, all csv files in the 'GGIR' output directory were read, transformed and then merged. In module 2, the 'GGIR' output files were checked and summarized in one excel sheet. In module 3, the merged data was cleaned according to the number of valid hours on each night and the number of valid days for each subject. In module 4, the cleaned activity data was imputed by the average Euclidean norm minus one (ENMO) over all the valid days for each subject. Finally, a comprehensive report of data processing was created using Rmarkdown, and the report includes few exploratory plots and multiple commonly used features extracted from minute level actigraphy data. Reference: Guo W, Leroux A, Shou S, Cui L, Kang S, Strippoli MP, Preisig M, Zipunnikov V, Merikangas K (2022) Processing of accelerometry data with GGIR in Motor Activity Research Consortium for Health (mMARCH) Journal for the Measurement of Physical Behaviour, 6(1): 37-44.

Maintained by Wei Guo. Last updated 2 years ago.

openjdk

2 stars 4.41 score 26 scripts

apjacobson

parmsurvfit:Parametric Models for Survival Data

Executes simple parametric models for right-censored survival data. Functionality emulates capabilities in 'Minitab', including fitting right-censored data, assessing fit, plotting survival functions, and summary statistics and probabilities.

Maintained by Ashley Jacobson. Last updated 6 years ago.

3 stars 4.41 score 17 scripts

robertwbuchkowski

soilfoodwebs:Soil Food Web Analysis

Analyzing soil food webs or any food web measured at equilibrium. The package calculates carbon and nitrogen fluxes and stability properties using methods described by Hunt et al. (1987) <doi:10.1007/BF00260580>, de Ruiter et al. (1995) <doi:10.1126/science.269.5228.1257>, Holtkamp et al. (2011) <doi:10.1016/j.soilbio.2010.10.004>, and Buchkowski and Lindo (2021) <doi:10.1111/1365-2435.13706>. The package can also manipulate the structure of the food web as well as simulate food webs away from equilibrium and run decomposition experiments.

Maintained by Robert Buchkowski. Last updated 11 months ago.

5 stars 4.40 score 4 scripts

bioc

INSPEcT:Modeling RNA synthesis, processing and degradation with RNA-seq data

INSPEcT (INference of Synthesis, Processing and dEgradation rates from Transcriptomic data) RNA-seq data in time-course experiments or steady-state conditions, with or without the support of nascent RNA data.

Maintained by Stefano de Pretis. Last updated 5 months ago.

sequencing rnaseq generegulation timecourse systemsbiology

4.38 score 9 scripts

anttonalberdi

hilldiv:Integral Analysis of Diversity Based on Hill Numbers

Tools for analysing, comparing, visualising and partitioning diversity based on Hill numbers. 'hilldiv' is an R package that provides a set of functions to assist analysis of diversity for diet reconstruction, microbial community profiling or more general ecosystem characterisation analyses based on Hill numbers, using OTU/ASV tables and associated phylogenetic trees as inputs. The package includes functions for (phylo)diversity measurement, (phylo)diversity profile plotting, (phylo)diversity comparison between samples and groups, (phylo)diversity partitioning and (dis)similarity measurement. All of these grounded in abundance-based and incidence-based Hill numbers. The statistical framework developed around Hill numbers encompasses many of the most broadly employed diversity (e.g. richness, Shannon index, Simpson index), phylogenetic diversity (e.g. Faith's PD, Allen's H, Rao's quadratic entropy) and dissimilarity (e.g. Sorensen index, Unifrac distances) metrics. This enables the most common analyses of diversity to be performed while grounded in a single statistical framework. The methods are described in Jost et al. (2007) <DOI:10.1890/06-1736.1>, Chao et al. (2010) <DOI:10.1098/rstb.2010.0272> and Chiu et al. (2014) <DOI:10.1890/12-0960.1>; and reviewed in the framework of molecularly characterised biological systems in Alberdi & Gilbert (2019) <DOI:10.1111/1755-0998.13014>.

Maintained by Antton Alberdi. Last updated 4 years ago.

11 stars 4.35 score 41 scripts

angelospsy

condir:Computation of P Values and Bayes Factors for Conditioning Data

Set of functions for the easy analyses of conditioning data.

Maintained by Angelos-Miltiadis Krypotos. Last updated 2 years ago.

2 stars 4.34 score 11 scripts

rsetienne

DAMOCLES:Dynamic Assembly Model of Colonization, Local Extinction and Speciation

Simulates and computes (maximum) likelihood of a dynamical model of community assembly that takes into account phylogenetic history.

Maintained by Rampal S. Etienne. Last updated 4 months ago.

cpp

1 stars 4.34 score 11 scripts

johnaponte

convdistr:Convolute Probabilistic Distributions

Convolute probabilistic distributions using the random generator function of each distribution. A new random number generator function is created that perform the mathematical operation on the individual random samples from the random generator function of each distribution. See the documentation for examples.

Maintained by Aponte John. Last updated 11 months ago.

2 stars 4.34 score 11 scripts

gasparl

neatStats:Neat and Painless Statistical Reporting

User-friendly, clear and simple statistics, primarily for publication in psychological science. The main functions are wrappers for other packages, but there are various additions as well. Every relevant step from data aggregation to reportable printed statistics is covered for basic experimental designs.

Maintained by Gáspár Lukács. Last updated 2 years ago.

bayesfactor confidence-intervals pipeline statistical-analysis statistics

4 stars 4.30 score

cxzdsa2332

idopNetwork:A Network Tool to Dissect Spatial Community Ecology

Most existing approaches for network reconstruction can only infer an overall network and, also, fail to capture a complete set of network properties. To address these issues, a new model has been developed, which converts static data into their 'dynamic' form. 'idopNetwork' is an 'R' interface to this model, it can inferring informative, dynamic, omnidirectional and personalized networks. For more information on functional clustering part, see Kim et al. (2008) <doi:10.1534/genetics.108.093690>, Wang et al. (2011) <doi:10.1093/bib/bbr032>. For more information on our model, see Chen et al. (2019) <doi:10.1038/s41540-019-0116-1>, and Cao et al. (2022) <doi:10.1080/19490976.2022.2106103>.

Maintained by Ang Dong. Last updated 2 years ago.

4 stars 4.30 score 3 scripts

haghbinh

Rfssa:Functional Singular Spectrum Analysis

Methods and tools for implementing functional singular spectrum analysis and related techniques.

Maintained by Hossein Haghbin. Last updated 1 years ago.

cpp

7 stars 4.30 score 19 scripts

kisungyou

T4cluster:Tools for Cluster Analysis

Cluster analysis is one of the most fundamental problems in data science. We provide a variety of algorithms from clustering to the learning on the space of partitions. See Hennig, Meila, and Rocci (2016, ISBN:9781466551886) for general exposition to cluster analysis.

Maintained by Kisung You. Last updated 4 years ago.

openblas cpp openmp

6 stars 4.26 score 9 scripts 2 dependents

richjjackson

psc:Personalised Synthetic Controls

Allows the comparison of data cohorts (DC) against a Counter Factual Model (CFM) and measures the difference in terms of an efficacy parameter. Allows the application of Personalised Synthetic Controls.

Maintained by Richard Jackson. Last updated 5 days ago.

1 stars 4.26 score 24 scripts

tanja819

TreeSim:Simulating Phylogenetic Trees

Simulation methods for phylogenetic trees where (i) all tips are sampled at one time point or (ii) tips are sampled sequentially through time. (i) For sampling at one time point, simulations are performed under a constant rate birth-death process, conditioned on having a fixed number of final tips (sim.bd.taxa()), or a fixed age (sim.bd.age()), or a fixed age and number of tips (sim.bd.taxa.age()). When conditioning on the number of final tips, the method allows for shifts in rates and mass extinction events during the birth-death process (sim.rateshift.taxa()). The function sim.bd.age() (and sim.rateshift.taxa() without extinction) allow the speciation rate to change in a density-dependent way. The LTT plots of the simulations can be displayed using LTT.plot(), LTT.plot.gen() and LTT.average.root(). TreeSim further samples trees with n final tips from a set of trees generated by the common sampling algorithm stopping when a fixed number m>>n of tips is first reached (sim.gsa.taxa()). This latter method is appropriate for m-tip trees generated under a big class of models (details in the sim.gsa.taxa() man page). For incomplete phylogeny, the missing speciation events can be added through simulations (corsim()). (ii) sim.rateshifts.taxa() is generalized to sim.bdsky.stt() for serially sampled trees, where the trees are conditioned on either the number of sampled tips or the age. Furthermore, for a multitype-branching process with sequential sampling, trees on a fixed number of tips can be simulated using sim.bdtypes.stt.taxa(). This function further allows to simulate under epidemiological models with an exposed class. The function sim.genespeciestree() simulates coalescent gene trees within birth-death species trees, and sim.genetree() simulates coalescent gene trees.

Maintained by Tanja Stadler. Last updated 6 years ago.

4.19 score 172 scripts 3 dependents

an-crawford

reslife:Calculate Mean Residual Life (MRL) and Related Values for Different Distributions

A pair of functions for calculating mean residual life (MRL) , median residual life, and percentile residual life using the outputs of either the 'flexsurv' package or parameters provided by the user. Input information about the distribution, the given 'life' value, the percentile, and the type of residual life, and the function will return your desired values. For the 'flexsurv' option, the function allows the user to input their own data for making predictions. This function is based on Jackson (2016) <doi:10.18637/jss.v070.i08>.

Maintained by Andrew Crawford. Last updated 1 years ago.

1 stars 4.18 score 2 scripts

angelospsy

multifear:Multiverse Analyses for Conditioning Data

A suite of functions for performing analyses, based on a multiverse approach, for conditioning data. Specifically, given the appropriate data, the functions are able to perform t-tests, analyses of variance, and mixed models for the provided data and return summary statistics and plots. The function is also able to return for all those tests p-values, confidence intervals, and Bayes factors. The methods are described in Lonsdorf, Gerlicher, Klingelhofer-Jens, & Krypotos (2022) <doi:10.1016/j.brat.2022.104072>.

Maintained by Angelos-Miltiadis Krypotos. Last updated 2 years ago.

conditioning multiverse

3 stars 4.18 score 7 scripts

glucodensities

biosensors.usc:Distributional Data Analysis Techniques for Biosensor Data

Unified and user-friendly framework for using new distributional representations of biosensors data in different statistical modeling tasks: regression models, hypothesis testing, cluster analysis, visualization, and descriptive analysis. Distributional representations are a functional extension of compositional time-range metrics and we have used them successfully so far in modeling glucose profiles and accelerometer data. However, these functional representations can be used to represent any biosensor data such as ECG or medical imaging such as fMRI. Matabuena M, Petersen A, Vidal JC, Gude F. "Glucodensities: A new representation of glucose profiles using distributional data analysis" (2021) <doi:10.1177/0962280221998064>.

Maintained by Juan C. Vidal. Last updated 3 years ago.

openblas cpp openmp

4.18 score 3 scripts

ramiyaari

simode:Statistical Inference for Systems of Ordinary Differential Equations using Separable Integral-Matching

Implements statistical inference for systems of ordinary differential equations, that uses the integral-matching criterion and takes advantage of the separability of parameters, in order to obtain initial parameter estimates for nonlinear least squares optimization. Dattner & Yaari (2018) <arXiv:1807.04202>. Dattner et al. (2017) <doi:10.1098/rsif.2016.0525>. Dattner & Klaassen (2015) <doi:10.1214/15-EJS1053>.

Maintained by Rami Yaari. Last updated 5 years ago.

3 stars 4.18 score 4 scripts

weehaong

tdsa:Time-Dependent Sensitivity Analysis

Functions that can be used to calculate time-dependent state and parameter sensitivities for both continuous- and discrete-time deterministic models. See Ng et al. (in press) <doi:10.1086/726143> for more information about time-dependent sensitivity analysis.

Maintained by Wee Hao Ng. Last updated 2 years ago.

4.18 score 7 scripts

bioc

PING:Probabilistic inference for Nucleosome Positioning with MNase-based or Sonicated Short-read Data

Probabilistic inference of ChIP-Seq using an empirical Bayes mixture model approach.

Maintained by Renan Sauteraud. Last updated 4 days ago.

clustering statisticalmethod visualization sequencing gsl

4.18 score 7 scripts

moondog1969

streamDAG:Analytical Methods for Stream DAGs

Provides indices and tools for directed acyclic graphs (DAGs), particularly DAG representations of intermittent streams. A detailed introduction to the package can be found in the publication: "Non-perennial stream networks as directed acyclic graphs: The R-package streamDAG" (Aho et al., 2023) <doi:10.1016/j.envsoft.2023.105775>, and in the introductory package vignette.

Maintained by Ken Aho. Last updated 6 months ago.

1 stars 4.18 score 4 scripts

nassimayad87

EpiSimR:A 'Shiny' App to Simulate the Dynamics of Epidemic and Endemic Diseases Spread

The 'EpiSimR' package provides an interactive 'shiny' app based on deterministic compartmental mathematical modeling for simulating and visualizing the dynamics of epidemic and endemic disease spread. It allows users to explore various intervention strategies, including vaccination and isolation, by adjusting key epidemiological parameters. The methodology follows the approach described by Brauer (2008) <doi:10.1007/978-3-540-78911-6_2>. Thanks to 'shiny' package.

Maintained by Nassim AYAD. Last updated 29 days ago.

infectious-disease-models seir-model shiny-apps simulation sir-model

4.18 score 1 scripts

vmoprojs

GeoModels:Procedures for Gaussian and Non Gaussian Geostatistical (Large) Data Analysis

Functions for Gaussian and Non Gaussian (bivariate) spatial and spatio-temporal data analysis are provided for a) (fast) simulation of random fields, b) inference for random fields using standard likelihood and a likelihood approximation method called weighted composite likelihood based on pairs and b) prediction using (local) best linear unbiased prediction. Weighted composite likelihood can be very efficient for estimating massive datasets. Both regression and spatial (temporal) dependence analysis can be jointly performed. Flexible covariance models for spatial and spatial-temporal data on Euclidean domains and spheres are provided. There are also many useful functions for plotting and performing diagnostic analysis. Different non Gaussian random fields can be considered in the analysis. Among them, random fields with marginal distributions such as Skew-Gaussian, Student-t, Tukey-h, Sin-Arcsin, Two-piece, Weibull, Gamma, Log-Gaussian, Binomial, Negative Binomial and Poisson. See the URL for the papers associated with this package, as for instance, Bevilacqua and Gaetan (2015) <doi:10.1007/s11222-014-9460-6>, Bevilacqua et al. (2016) <doi:10.1007/s13253-016-0256-3>, Vallejos et al. (2020) <doi:10.1007/978-3-030-56681-4>, Bevilacqua et. al (2020) <doi:10.1002/env.2632>, Bevilacqua et. al (2021) <doi:10.1111/sjos.12447>, Bevilacqua et al. (2022) <doi:10.1016/j.jmva.2022.104949>, Morales-Navarrete et al. (2023) <doi:10.1080/01621459.2022.2140053>, and a large class of examples and tutorials.

Maintained by Moreno Bevilacqua. Last updated 2 months ago.

fortran openblas glibc

3 stars 4.17 score 83 scripts

bioc

MEIGOR:MEIGOR - MEtaheuristics for bIoinformatics Global Optimization

MEIGOR provides a comprehensive environment for performing global optimization tasks in bioinformatics and systems biology. It leverages advanced metaheuristic algorithms to efficiently search the solution space and is specifically tailored to handle the complexity and high-dimensionality of biological datasets. This package supports various optimization routines and is integrated with Bioconductor's infrastructure for a seamless analysis workflow.

Maintained by Jose A. Egea. Last updated 5 months ago.

systemsbiology optimization software

4.12 score 44 scripts

coffeemuggler

sandbox:Probabilistic Numerical Modelling of Sediment Properties

A flexible framework for definition and application of time/depth- based rules for sets of parameters for single grains that can be used to create artificial sediment profiles. Such profiles can be used for virtual sample preparation and synthetic, for instance, luminescence measurements.

Maintained by Michael Dietze. Last updated 9 months ago.

1 stars 4.09 score 248 scripts

alexvolkmann

MJMbamlss:Multivariate Joint Models with 'bamlss'

Multivariate joint models of longitudinal and time-to-event data based on functional principal components implemented with 'bamlss'. Implementation for Volkmann, Umlauf, Greven (2023) <arXiv:2311.06409>.

Maintained by Alexander Volkmann. Last updated 22 days ago.

2 stars 4.08 score 15 scripts

helenkettle

stagePop:Modelling the Population Dynamics of a Stage-Structured Species in Continuous Time

Provides facilities to implement and run population models of stage-structured species...

Maintained by David Nutter. Last updated 10 years ago.

1 stars 4.08 score 24 scripts

jrvanderdoes

fChange:Functional Change Point Detection and Analysis

Analyze functional data and its change points. Includes functionality to store and process data, summarize and validate assumptions, characterize and perform inference of change points, and provide visualizations. Data is stored as discretely collected observations without requiring the selection of basis functions. For more details see chapter 8 of Horvath and Rice (2024) <doi:10.1007/978-3-031-51609-2>. Additional papers are forthcoming. Focused works are also included in the documentation of corresponding functions.

Maintained by Jeremy VanderDoes. Last updated 20 hours ago.

openblas cpp openmp

1 stars 4.04 score

pik-piam

mrsoil:MadRat Soil Organic Carbon Budget Library

This packages provides functions for soil organic carbon budget for mineral soils using the steady-state method (Tier 2) of the 2019 Refinement to the 2006 IPP Guidelines for National Greenhouse Gas Inventories.

Maintained by Kristine Karstens. Last updated 6 months ago.

3 stars 4.03 score 3 dependents

afmagee

CRABS:Congruent Rate Analyses in Birth-Death Scenarios

Features tools for exploring congruent phylogenetic birth-death models. It can construct the pulled speciation- and net-diversification rates from a reference model. Given alternative speciation- or extinction rates, it can construct new models that are congruent with the reference model. Functionality is included to sample new rate functions, and to visualize the distribution of one congruence class. See also Louca & Pennell (2020) <doi:10.1038/s41586-020-2176-1>.

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

7 stars 4.02 score 5 scripts

jeksterslab

bootStateSpace:Bootstrap for State Space Models

Provides a streamlined and user-friendly framework for bootstrapping in state space models, particularly when the number of subjects/units (n) exceeds one, a scenario commonly encountered in social and behavioral sciences. For an introduction to state space models in social and behavioral sciences, refer to Chow, Ho, Hamaker, and Dolan (2010) <doi:10.1080/10705511003661553>.

Maintained by Ivan Jacob Agaloos Pesigan. Last updated 1 months ago.

bootstrap state-space-model

4.01 score 51 scripts

puigjos

ConsReg:Fitting Regression Models & Regression with Arma Errors, Subject to Constraints and Restrictions to the Coefficients

Fits or generalized linear models either a regression with arma errors (Time series) where the parameters could be subject to constraints or restrictions. The model is specified by an objective function (Gaussian, Binomial or Poisson) or an Arma order (p,q), a vector of bound constraints for the coefficients and the possibility to incorporate restrictions among coefficients (i.e b1 > b2).

Maintained by Josep Puig. Last updated 5 years ago.

2 stars 4.00 score 4 scripts

bioc

fCCAC:functional Canonical Correlation Analysis to evaluate Covariance between nucleic acid sequencing datasets

Computational evaluation of variability across DNA or RNA sequencing datasets is a crucial step in genomics, as it allows both to evaluate reproducibility of replicates, and to compare different datasets to identify potential correlations. fCCAC applies functional Canonical Correlation Analysis to allow the assessment of: (i) reproducibility of biological or technical replicates, analyzing their shared covariance in higher order components; and (ii) the associations between different datasets. fCCAC represents a more sophisticated approach that complements Pearson correlation of genomic coverage.

Maintained by Pedro Madrigal. Last updated 5 months ago.

epigenetics transcription sequencing coverage chipseq functionalgenomics rnaseq atacseq mnaseseq

4.00 score 1 scripts

nkehrein

lemna:Lemna Ecotox Effect Model

The reference implementation of model equations and default parameters for the toxicokinetic-toxicodynamic (TKTD) model of the Lemna (duckweed) aquatic plant. Lemna is a standard test macrophyte used in ecotox effect studies. The model was described and published by the SETAC Europe Interest Group Effect Modeling. It is a refined description of the Lemna TKTD model published by Schmitt et al. (2013) <doi:10.1016/j.ecolmodel.2013.01.017>.

Maintained by Nils Kehrein. Last updated 6 months ago.

simulation

1 stars 4.00 score 4 scripts

eligurarie

cyclomort:Survival Modeling with a Periodic Hazard Function

Modeling periodic mortality (or other time-to event) processes from right-censored data. Given observations of a process with a known period (e.g. 365 days, 24 hours), functions determine the number, intensity, timing, and duration of peaks of periods of elevated hazard within a period. The underlying model is a mixed wrapped Cauchy function fitted using maximum likelihoods (details in Gurarie et al. (2020) <doi:10.1111/2041-210X.13305>). The development of these tools was motivated by the strongly seasonal mortality patterns observed in many wild animal populations, such that the respective periods of higher mortality can be identified as "mortality seasons".

Maintained by Eliezer Gurarie. Last updated 5 years ago.

2 stars 4.00 score 2 scripts

semran9

tfNeuralODE:Create Neural Ordinary Differential Equations with 'tensorflow'

Provides a framework for the creation and use of Neural ordinary differential equations with the 'tensorflow' and 'keras' packages. The idea of Neural ordinary differential equations comes from Chen et al. (2018) <doi:10.48550/arXiv.1806.07366>, and presents a novel way of learning and solving differential systems.

Maintained by Shayaan Emran. Last updated 1 years ago.

1 stars 4.00 score 5 scripts

ttacail

isobxr:Stable Isotope Box Modelling in R

A set of functions to run simple and composite box-models to describe the dynamic or static distribution of stable isotopes in open or closed systems. The package also allows the sweeping of many parameters in both static and dynamic conditions. The mathematical models used in this package are derived from Albarede, 1995, Introduction to Geochemical Modelling, Cambridge University Press, Cambridge <doi:10.1017/CBO9780511622960>.

Maintained by Theo Tacail. Last updated 11 months ago.

1 stars 4.00 score 2 scripts

calfarog

GREENeR:Geospatial Regression Equation for European Nutrient Losses (GREEN)

Tools and methods to apply the model Geospatial Regression Equation for European Nutrient losses (GREEN); Grizzetti et al. (2005) <doi:10.1016/j.jhydrol.2004.07.036>; Grizzetti et al. (2008); Grizzetti et al. (2012) <doi:10.1111/j.1365-2486.2011.02576.x>; Grizzetti et al. (2021) <doi:10.1016/j.gloenvcha.2021.102281>.

Maintained by C. Alfaro. Last updated 7 months ago.

calibration geospatial nutrient plots

1 stars 4.00 score 9 scripts

caseybreen

gompertztrunc:Conducting Maximum Likelihood Estimation with Truncated Mortality Data

Estimates hazard ratios and mortality differentials for doubly-truncated data without population denominators. This method is described in Goldstein et al. (2023) <doi:10.1007/s11113-023-09785-z>.

Maintained by Maria Osborne. Last updated 1 years ago.

4.00 score 7 scripts

amderoos

deBif:Bifurcation Analysis of Ordinary Differential Equation Systems

Shiny application that performs bifurcation and phaseplane analysis of systems of ordinary differential equations. The package allows for computation of equilibrium curves as a function of a single free parameter, detection of transcritical, saddle-node and hopf bifurcation points along these curves, and computation of curves representing these transcritical, saddle-node and hopf bifurcation points as a function of two free parameters. The shiny-based GUI allows visualization of the results in both 2D- and 3D-plots. The implemented methods for solution localisation and curve continuation are based on the book "Elements of applied bifurcation theory" (Kuznetsov, Y. A., 1995; ISBN: 0-387-94418-4).

Maintained by Andre M. de Roos. Last updated 1 months ago.

openblas

4.00 score 3 scripts

objornstad

epimdr2:Functions and Data for "Epidemics: Models and Data in R (2nd Edition)"

Functions, data sets and shiny apps for "Epidemics: Models and Data in R (2nd edition)" by Ottar N. Bjornstad (ISBN: 978-3-031-12055-8) <https://link.springer.com/book/9783031120558>. The package contains functions to study the S(E)IR model, spatial and age-structured SIR models; time-series SIR and chain-binomial stochastic models; catalytic disease models; coupled map lattice models of spatial transmission and network models for social spread of infection. The package is also an advanced quantitative companion to the Coursera Epidemics Massive Online Open Course <https://www.coursera.org/learn/epidemics>.

Maintained by Ottar N. Bjornstad. Last updated 2 years ago.

19 stars 3.98 score