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igraph

igraph:Network Analysis and Visualization

Routines for simple graphs and network analysis. It can handle large graphs very well and provides functions for generating random and regular graphs, graph visualization, centrality methods and much more.

Maintained by Kirill Müller. Last updated 7 hours ago.

complex-networksgraph-algorithmsgraph-theorymathematicsnetwork-analysisnetwork-graphfortranlibxml2glpkopenblascpp

584 stars 21.14 score 31k scripts 1.9k dependents

r-lib

testthat:Unit Testing for R

Software testing is important, but, in part because it is frustrating and boring, many of us avoid it. 'testthat' is a testing framework for R that is easy to learn and use, and integrates with your existing 'workflow'.

Maintained by Hadley Wickham. Last updated 30 days ago.

unit-testingcpp

900 stars 20.99 score 74k scripts 471 dependents

rspatial

terra:Spatial Data Analysis

Methods for spatial data analysis with vector (points, lines, polygons) and raster (grid) data. Methods for vector data include geometric operations such as intersect and buffer. Raster methods include local, focal, global, zonal and geometric operations. The predict and interpolate methods facilitate the use of regression type (interpolation, machine learning) models for spatial prediction, including with satellite remote sensing data. Processing of very large files is supported. See the manual and tutorials on <https://rspatial.org/> to get started. 'terra' replaces the 'raster' package ('terra' can do more, and it is faster and easier to use).

Maintained by Robert J. Hijmans. Last updated 18 hours ago.

geospatialrasterspatialvectoronetbbprojgdalgeoscpp

560 stars 17.65 score 17k scripts 856 dependents

stan-dev

loo:Efficient Leave-One-Out Cross-Validation and WAIC for Bayesian Models

Efficient approximate leave-one-out cross-validation (LOO) for Bayesian models fit using Markov chain Monte Carlo, as described in Vehtari, Gelman, and Gabry (2017) <doi:10.1007/s11222-016-9696-4>. The approximation uses Pareto smoothed importance sampling (PSIS), a new procedure for regularizing importance weights. As a byproduct of the calculations, we also obtain approximate standard errors for estimated predictive errors and for the comparison of predictive errors between models. The package also provides methods for using stacking and other model weighting techniques to average Bayesian predictive distributions.

Maintained by Jonah Gabry. Last updated 17 days ago.

bayesbayesianbayesian-data-analysisbayesian-inferencebayesian-methodsbayesian-statisticscross-validationinformation-criterionmodel-comparisonstan

152 stars 17.30 score 2.6k scripts 297 dependents

r-lib

waldo:Find Differences Between R Objects

Compare complex R objects and reveal the key differences. Designed particularly for use in testing packages where being able to quickly isolate key differences makes understanding test failures much easier.

Maintained by Hadley Wickham. Last updated 5 months ago.

difftesting

291 stars 13.95 score 143 scripts 480 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

projectmosaic

mosaic:Project MOSAIC Statistics and Mathematics Teaching Utilities

Data sets and utilities from Project MOSAIC (<http://www.mosaic-web.org>) used to teach mathematics, statistics, computation and modeling. Funded by the NSF, Project MOSAIC is a community of educators working to tie together aspects of quantitative work that students in science, technology, engineering and mathematics will need in their professional lives, but which are usually taught in isolation, if at all.

Maintained by Randall Pruim. Last updated 1 years ago.

93 stars 13.32 score 7.2k scripts 7 dependents

kkholst

lava:Latent Variable Models

A general implementation of Structural Equation Models with latent variables (MLE, 2SLS, and composite likelihood estimators) with both continuous, censored, and ordinal outcomes (Holst and Budtz-Joergensen (2013) <doi:10.1007/s00180-012-0344-y>). Mixture latent variable models and non-linear latent variable models (Holst and Budtz-Joergensen (2020) <doi:10.1093/biostatistics/kxy082>). The package also provides methods for graph exploration (d-separation, back-door criterion), simulation of general non-linear latent variable models, and estimation of influence functions for a broad range of statistical models.

Maintained by Klaus K. Holst. Last updated 3 months ago.

latent-variable-modelssimulationstatisticsstructural-equation-models

33 stars 12.87 score 610 scripts 478 dependents

data-cleaning

validate:Data Validation Infrastructure

Declare data validation rules and data quality indicators; confront data with them and analyze or visualize the results. The package supports rules that are per-field, in-record, cross-record or cross-dataset. Rules can be automatically analyzed for rule type and connectivity. Supports checks implied by an SDMX DSD file as well. See also Van der Loo and De Jonge (2018) <doi:10.1002/9781118897126>, Chapter 6 and the JSS paper (2021) <doi:10.18637/jss.v097.i10>.

Maintained by Mark van der Loo. Last updated 26 days ago.

data-cleaningvalidation

419 stars 12.39 score 448 scripts 8 dependents

tarnduong

ks:Kernel Smoothing

Kernel smoothers for univariate and multivariate data, with comprehensive visualisation and bandwidth selection capabilities, including for densities, density derivatives, cumulative distributions, clustering, classification, density ridges, significant modal regions, and two-sample hypothesis tests. Chacon & Duong (2018) <doi:10.1201/9780429485572>.

Maintained by Tarn Duong. Last updated 6 months ago.

6 stars 10.19 score 920 scripts 262 dependents

pitakakariki

simr:Power Analysis for Generalised Linear Mixed Models by Simulation

Calculate power for generalised linear mixed models, using simulation. Designed to work with models fit using the 'lme4' package. Described in Green and MacLeod, 2016 <doi:10.1111/2041-210X.12504>.

Maintained by Peter Green. Last updated 2 years ago.

71 stars 9.87 score 756 scripts

gavinsimpson

analogue:Analogue and Weighted Averaging Methods for Palaeoecology

Fits Modern Analogue Technique and Weighted Averaging transfer function models for prediction of environmental data from species data, and related methods used in palaeoecology.

Maintained by Gavin L. Simpson. Last updated 6 months ago.

14 stars 8.87 score 185 scripts 4 dependents

kollerma

robustlmm:Robust Linear Mixed Effects Models

Implements the Robust Scoring Equations estimator to fit linear mixed effects models robustly. Robustness is achieved by modification of the scoring equations combined with the Design Adaptive Scale approach.

Maintained by Manuel Koller. Last updated 1 years ago.

openblascpp

28 stars 8.79 score 138 scripts

flr

FLCore:Core Package of FLR, Fisheries Modelling in R

Core classes and methods for FLR, a framework for fisheries modelling and management strategy simulation in R. Developed by a team of fisheries scientists in various countries. More information can be found at <http://flr-project.org/>.

Maintained by Iago Mosqueira. Last updated 10 days ago.

fisheriesflrfisheries-modelling

16 stars 8.78 score 956 scripts 23 dependents

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

ampl-psych

EMC2:Bayesian Hierarchical Analysis of Cognitive Models of Choice

Fit Bayesian (hierarchical) cognitive models using a linear modeling language interface using particle Metropolis Markov chain Monte Carlo sampling with Gibbs steps. The diffusion decision model (DDM), linear ballistic accumulator model (LBA), racing diffusion model (RDM), and the lognormal race model (LNR) are supported. Additionally, users can specify their own likelihood function and/or choose for non-hierarchical estimation, as well as for a diagonal, blocked or full multivariate normal group-level distribution to test individual differences. Prior specification is facilitated through methods that visualize the (implied) prior. A wide range of plotting functions assist in assessing model convergence and posterior inference. Models can be easily evaluated using functions that plot posterior predictions or using relative model comparison metrics such as information criteria or Bayes factors. References: Stevenson et al. (2024) <doi:10.31234/osf.io/2e4dq>.

Maintained by Niek Stevenson. Last updated 20 days ago.

cpp

13 stars 8.25 score 392 scripts

walkerke

mapgl:Interactive Maps with 'Mapbox GL JS' and 'MapLibre GL JS'

Provides an interface to the 'Mapbox GL JS' (<https://docs.mapbox.com/mapbox-gl-js/guides>) and the 'MapLibre GL JS' (<https://maplibre.org/maplibre-gl-js/docs/>) interactive mapping libraries to help users create custom interactive maps in R. Users can create interactive globe visualizations; layer 'sf' objects to create filled maps, circle maps, 'heatmaps', and three-dimensional graphics; and customize map styles and views. The package also includes utilities to use 'Mapbox' and 'MapLibre' maps in 'Shiny' web applications.

Maintained by Kyle Walker. Last updated 12 days ago.

116 stars 8.08 score 138 scripts

yonicd

ggedit:Interactive 'ggplot2' Layer and Theme Aesthetic Editor

Interactively edit 'ggplot2' layer and theme aesthetics definitions.

Maintained by Jonathan Sidi. Last updated 11 months ago.

ggplot2shiny

250 stars 7.95 score 116 scripts 3 dependents

bnowok

synthpop:Generating Synthetic Versions of Sensitive Microdata for Statistical Disclosure Control

A tool for producing synthetic versions of microdata containing confidential information so that they are safe to be released to users for exploratory analysis. The key objective of generating synthetic data is to replace sensitive original values with synthetic ones causing minimal distortion of the statistical information contained in the data set. Variables, which can be categorical or continuous, are synthesised one-by-one using sequential modelling. Replacements are generated by drawing from conditional distributions fitted to the original data using parametric or classification and regression trees models. Data are synthesised via the function syn() which can be largely automated, if default settings are used, or with methods defined by the user. Optional parameters can be used to influence the disclosure risk and the analytical quality of the synthesised data. For a description of the implemented method see Nowok, Raab and Dibben (2016) <doi:10.18637/jss.v074.i11>.

Maintained by Beata Nowok. Last updated 3 years ago.

44 stars 7.88 score 536 scripts

cran

bnlearn:Bayesian Network Structure Learning, Parameter Learning and Inference

Bayesian network structure learning, parameter learning and inference. This package implements constraint-based (PC, GS, IAMB, Inter-IAMB, Fast-IAMB, MMPC, Hiton-PC, HPC), pairwise (ARACNE and Chow-Liu), score-based (Hill-Climbing and Tabu Search) and hybrid (MMHC, RSMAX2, H2PC) structure learning algorithms for discrete, Gaussian and conditional Gaussian networks, along with many score functions and conditional independence tests. The Naive Bayes and the Tree-Augmented Naive Bayes (TAN) classifiers are also implemented. Some utility functions (model comparison and manipulation, random data generation, arc orientation testing, simple and advanced plots) are included, as well as support for parameter estimation (maximum likelihood and Bayesian) and inference, conditional probability queries, cross-validation, bootstrap and model averaging. Development snapshots with the latest bugfixes are available from <https://www.bnlearn.com/>.

Maintained by Marco Scutari. Last updated 3 months ago.

openblas

57 stars 7.72 score 32 dependents

rezamoammadi

BDgraph:Bayesian Structure Learning in Graphical Models using Birth-Death MCMC

Advanced statistical tools for Bayesian structure learning in undirected graphical models, accommodating continuous, ordinal, discrete, count, and mixed data. It integrates recent advancements in Bayesian graphical models as presented in the literature, including the works of Mohammadi and Wit (2015) <doi:10.1214/14-BA889>, Mohammadi et al. (2021) <doi:10.1080/01621459.2021.1996377>, Dobra and Mohammadi (2018) <doi:10.1214/18-AOAS1164>, and Mohammadi et al. (2023) <doi:10.48550/arXiv.2307.00127>.

Maintained by Reza Mohammadi. Last updated 7 months ago.

openblascppopenmp

8 stars 7.46 score 223 scripts 7 dependents

soerenpannier

emdi:Estimating and Mapping Disaggregated Indicators

Functions that support estimating, assessing and mapping regional disaggregated indicators. So far, estimation methods comprise direct estimation, the model-based unit-level approach Empirical Best Prediction (see "Small area estimation of poverty indicators" by Molina and Rao (2010) <doi:10.1002/cjs.10051>), the area-level model (see "Estimates of income for small places: An application of James-Stein procedures to Census Data" by Fay and Herriot (1979) <doi:10.1080/01621459.1979.10482505>) and various extensions of it (adjusted variance estimation methods, log and arcsin transformation, spatial, robust and measurement error models), as well as their precision estimates. The assessment of the used model is supported by a summary and diagnostic plots. For a suitable presentation of estimates, map plots can be easily created. Furthermore, results can easily be exported to excel. For a detailed description of the package and the methods used see "The R Package emdi for Estimating and Mapping Regionally Disaggregated Indicators" by Kreutzmann et al. (2019) <doi:10.18637/jss.v091.i07> and the second package vignette "A Framework for Producing Small Area Estimates Based on Area-Level Models in R".

Maintained by Soeren Pannier. Last updated 1 years ago.

15 stars 7.26 score 45 scripts 1 dependents

edzer

trajectories:Classes and Methods for Trajectory Data

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

Maintained by Edzer Pebesma. Last updated 7 months ago.

31 stars 7.25 score 76 scripts 1 dependents

projectmosaic

mosaicCore:Common Utilities for Other MOSAIC-Family Packages

Common utilities used in other MOSAIC-family packages are collected here.

Maintained by Randall Pruim. Last updated 1 years ago.

1 stars 7.07 score 113 scripts 26 dependents

sachaepskamp

psychonetrics:Structural Equation Modeling and Confirmatory Network Analysis

Multi-group (dynamical) structural equation models in combination with confirmatory network models from cross-sectional, time-series and panel data <doi:10.31234/osf.io/8ha93>. Allows for confirmatory testing and fit as well as exploratory model search.

Maintained by Sacha Epskamp. Last updated 3 days ago.

openblascpp

51 stars 6.88 score 41 scripts 1 dependents

flr

FLasher:Projection and Forecasting of Fish Populations, Stocks and Fleets

Projection of future population and fishery dynamics is carried out for a given set of management targets. A system of equations is solved, using Automatic Differentation (AD), for the levels of effort by fishery (fleet) that will result in the required abundances, catches or fishing mortalities.

Maintained by Iago Mosqueira. Last updated 23 days ago.

forecastfisheriesflrcpp

2 stars 6.86 score 254 scripts 6 dependents

rte-antares-rpackage

antaresProcessing:'Antares' Results Processing

Process results generated by 'Antares', a powerful open source software developed by RTE (Réseau de Transport d’Électricité) to simulate and study electric power systems (more information about 'Antares' here: <https://github.com/AntaresSimulatorTeam/Antares_Simulator>). This package provides functions to create new columns like net load, load factors, upward and downward margins or to compute aggregated statistics like economic surpluses of consumers, producers and sectors.

Maintained by Tatiana Vargas. Last updated 4 months ago.

infrastructuredataimportadequacyantaresbilandatatableenergylinear-algebramarginsmonte-carlo-simulationoptimizationprevisionnelrtesimulationsurplustyndp

8 stars 6.70 score 35 scripts 1 dependents

fbertran

Cascade:Selection, Reverse-Engineering and Prediction in Cascade Networks

A modeling tool allowing gene selection, reverse engineering, and prediction in cascade networks. Jung, N., Bertrand, F., Bahram, S., Vallat, L., and Maumy-Bertrand, M. (2014) <doi:10.1093/bioinformatics/btt705>.

Maintained by Frederic Bertrand. Last updated 2 years ago.

1 stars 6.56 score 40 scripts 2 dependents

sonsoleslp

tna:Transition Network Analysis (TNA)

Provides tools for performing Transition Network Analysis (TNA) to study relational dynamics, including functions for building and plotting TNA models, calculating centrality measures, and identifying dominant events and patterns. TNA statistical techniques (e.g., bootstrapping and permutation tests) ensure the reliability of observed insights and confirm that identified dynamics are meaningful. See (Saqr et al., 2025) <doi:10.1145/3706468.3706513> for more details on TNA.

Maintained by Sonsoles López-Pernas. Last updated 4 days ago.

educational-data-mininglearning-analyticsmarkov-modeltemporal-analysis

4 stars 6.51 score 5 scripts

paulowhite

timeROC:Time-Dependent ROC Curve and AUC for Censored Survival Data

Estimation of time-dependent ROC curve and area under time dependent ROC curve (AUC) in the presence of censored data, with or without competing risks. Confidence intervals of AUCs and tests for comparing AUCs of two rival markers measured on the same subjects can be computed, using the iid-representation of the AUC estimator. Plot functions for time-dependent ROC curves and AUC curves are provided. Time-dependent Positive Predictive Values (PPV) and Negative Predictive Values (NPV) can also be computed. See Blanche et al. (2013) <doi:10.1002/sim.5958> and references therein for the details of the methods implemented in the package.

Maintained by Paul Blanche. Last updated 5 years ago.

9 stars 6.46 score 342 scripts 9 dependents

agrdatasci

gosset:Tools for Data Analysis in Experimental Agriculture

Methods to analyse experimental agriculture data, from data synthesis to model selection and visualisation. The package is named after W.S. Gosset aka ‘Student’, a pioneer of modern statistics in small sample experimental design and analysis.

Maintained by Kauê de Sousa. Last updated 4 months ago.

experimental-designrankings-data

6 stars 6.44 score 23 scripts

bioc

RNAmodR:Detection of post-transcriptional modifications in high throughput sequencing data

RNAmodR provides classes and workflows for loading/aggregation data from high througput sequencing aimed at detecting post-transcriptional modifications through analysis of specific patterns. In addition, utilities are provided to validate and visualize the results. The RNAmodR package provides a core functionality from which specific analysis strategies can be easily implemented as a seperate package.

Maintained by Felix G.M. Ernst. Last updated 5 months ago.

softwareinfrastructureworkflowstepvisualizationsequencingalkanilineseqbioconductormodificationsribomethseqrnarnamodr

3 stars 6.39 score 9 scripts 3 dependents

nicebread

RSA:Response Surface Analysis

Advanced response surface analysis. The main function RSA computes and compares several nested polynomial regression models (full second- or third-order polynomial, shifted and rotated squared difference model, rising ridge surfaces, basic squared difference model, asymmetric or level-dependent congruence effect models). The package provides plotting functions for 3d wireframe surfaces, interactive 3d plots, and contour plots. Calculates many surface parameters (a1 to a5, principal axes, stationary point, eigenvalues) and provides standard, robust, or bootstrapped standard errors and confidence intervals for them.

Maintained by Felix Schönbrodt. Last updated 12 months ago.

17 stars 6.30 score 26 scripts 1 dependents

fbertran

Patterns:Deciphering Biological Networks with Patterned Heterogeneous Measurements

A modeling tool dedicated to biological network modeling (Bertrand and others 2020, <doi:10.1093/bioinformatics/btaa855>). It allows for single or joint modeling of, for instance, genes and proteins. It starts with the selection of the actors that will be the used in the reverse engineering upcoming step. An actor can be included in that selection based on its differential measurement (for instance gene expression or protein abundance) or on its time course profile. Wrappers for actors clustering functions and cluster analysis are provided. It also allows reverse engineering of biological networks taking into account the observed time course patterns of the actors. Many inference functions are provided and dedicated to get specific features for the inferred network such as sparsity, robust links, high confidence links or stable through resampling links. Some simulation and prediction tools are also available for cascade networks (Jung and others 2014, <doi:10.1093/bioinformatics/btt705>). Example of use with microarray or RNA-Seq data are provided.

Maintained by Frederic Bertrand. Last updated 11 months ago.

4 stars 6.16 score 18 scripts

andybega

states:Create Panels of Independent States

Create panel data consisting of independent states from 1816 to the present. The package includes the Gleditsch & Ward (G&W) and Correlates of War (COW) lists of independent states, as well as helper functions for working with state panel data and standardizing other data sources to create country-year/month/etc. data.

Maintained by Andreas Beger. Last updated 2 years ago.

country-codesindependent-statespolitical-science

14 stars 6.08 score 86 scripts

henrikbengtsson

aroma.affymetrix:Analysis of Large Affymetrix Microarray Data Sets

A cross-platform R framework that facilitates processing of any number of Affymetrix microarray samples regardless of computer system. The only parameter that limits the number of chips that can be processed is the amount of available disk space. The Aroma Framework has successfully been used in studies to process tens of thousands of arrays. This package has actively been used since 2006.

Maintained by Henrik Bengtsson. Last updated 1 years ago.

infrastructureproprietaryplatformsexonarraymicroarrayonechannelguidataimportdatarepresentationpreprocessingqualitycontrolvisualizationreportwritingacghcopynumbervariantsdifferentialexpressiongeneexpressionsnptranscriptionaffymetrixanalysiscopy-numberdnaexpressionhpclarge-scalenotebookreproducibilityrna

10 stars 5.79 score 112 scripts 3 dependents

staffanbetner

rethinking:Statistical Rethinking book package

Utilities for fitting and comparing models

Maintained by Richard McElreath. Last updated 4 months ago.

5.42 score 4.4k scripts

wlenhard

cNORM:Continuous Norming

A comprehensive toolkit for generating continuous test norms in psychometrics and biometrics, and analyzing model fit. The package offers both distribution-free modeling using Taylor polynomials and parametric modeling using the beta-binomial distribution. Originally developed for achievement tests, it is applicable to a wide range of mental, physical, or other test scores dependent on continuous or discrete explanatory variables. The package provides several advantages: It minimizes deviations from representativeness in subsamples, interpolates between discrete levels of explanatory variables, and significantly reduces the required sample size compared to conventional norming per age group. cNORM enables graphical and analytical evaluation of model fit, accommodates a wide range of scales including those with negative and descending values, and even supports conventional norming. It generates norm tables including confidence intervals. It also includes methods for addressing representativeness issues through Iterative Proportional Fitting.

Maintained by Wolfgang Lenhard. Last updated 4 months ago.

beta-binomialbiometricscontinuous-norminggrowth-curvenorm-scoresnorm-tablesnormalization-techniquespercentilepsychometricsregression-based-normingtaylor-series

2 stars 5.38 score 75 scripts

centerforstatistics-ugent

pim:Fit Probabilistic Index Models

Fit a probabilistic index model as described in Thas et al, 2012: <doi:10.1111/j.1467-9868.2011.01020.x>. The interface to the modeling function has changed in this new version. The old version is still available at R-Forge.

Maintained by Joris Meys. Last updated 3 months ago.

modellingstatistics

10 stars 5.33 score 43 scripts

bioc

CMA:Synthesis of microarray-based classification

This package provides a comprehensive collection of various microarray-based classification algorithms both from Machine Learning and Statistics. Variable Selection, Hyperparameter tuning, Evaluation and Comparison can be performed combined or stepwise in a user-friendly environment.

Maintained by Roman Hornung. Last updated 5 months ago.

classificationdecisiontree

5.09 score 61 scripts

annennenne

causalDisco:Tools for Causal Discovery on Observational Data

Various tools for inferring causal models from observational data. The package includes an implementation of the temporal Peter-Clark (TPC) algorithm. Petersen, Osler and Ekstrøm (2021) <doi:10.1093/aje/kwab087>. It also includes general tools for evaluating differences in adjacency matrices, which can be used for evaluating performance of causal discovery procedures.

Maintained by Anne Helby Petersen. Last updated 27 days ago.

19 stars 4.76 score 10 scripts

cran

compare:Comparing Objects for Differences

Functions to compare a model object to a comparison object. If the objects are not identical, the functions can be instructed to explore various modifications of the objects (e.g., sorting rows, dropping names) to see if the modified versions are identical.

Maintained by Paul Murrell. Last updated 10 years ago.

4.68 score 5 dependents

marc-girondot

HelpersMG:Tools for Environmental Analyses, Ecotoxicology and Various R Functions

Contains miscellaneous functions useful for managing 'NetCDF' files (see <https://en.wikipedia.org/wiki/NetCDF>), get moon phase and time for sun rise and fall, tide level, analyse and reconstruct periodic time series of temperature with irregular sinusoidal pattern, show scales and wind rose in plot with change of color of text, Metropolis-Hastings algorithm for Bayesian MCMC analysis, plot graphs or boxplot with error bars, search files in disk by there names or their content, read the contents of all files from a folder at one time.

Maintained by Marc Girondot. Last updated 2 days ago.

4 stars 4.62 score 160 scripts 5 dependents

ssa-statistical-team-projects

povmap:Extension to the 'emdi' Package

The R package 'povmap' supports small area estimation of means and poverty headcount rates. It adds several new features to the 'emdi' package (see "The R Package emdi for Estimating and Mapping Regionally Disaggregated Indicators" by Kreutzmann et al. (2019) <doi:10.18637/jss.v091.i07>). These include new options for incorporating survey weights, ex-post benchmarking of estimates, two additional transformations, several new convenient functions to assist with reporting results, and a wrapper function to facilitate access from 'Stata'.

Maintained by Ifeanyi Edochie. Last updated 5 months ago.

1 stars 4.60 score 10 scripts

maxwestphal

cases:Stratified Evaluation of Subgroup Classification Accuracy

Enables simultaneous statistical inference for the accuracy of multiple classifiers in multiple subgroups (strata). For instance, allows to perform multiple comparisons in diagnostic accuracy studies with co-primary endpoints sensitivity and specificity (Westphal M, Zapf A. Statistical inference for diagnostic test accuracy studies with multiple comparisons. Statistical Methods in Medical Research. 2024;0(0). <doi:10.1177/09622802241236933>).

Maintained by Max Westphal. Last updated 3 months ago.

1 stars 4.59 score 13 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

langendorfr

netcom:NETwork COMparison Inference

Infer system functioning with empirical NETwork COMparisons. These methods are part of a growing paradigm in network science that uses relative comparisons of networks to infer mechanistic classifications and predict systemic interventions. They have been developed and applied in Langendorf and Burgess (2021) <doi:10.1038/s41598-021-99251-7>, Langendorf (2020) <doi:10.1201/9781351190831-6>, and Langendorf and Goldberg (2019) <arXiv:1912.12551>.

Maintained by Ryan Langendorf. Last updated 9 months ago.

5 stars 4.46 score 115 scripts

timbeechey

clubpro:Classification Using Binary Procrustes Rotation

Implements a classification method described by Grice (2011, ISBN:978-0-12-385194-9) using binary procrustes rotation; a simplified version of procrustes rotation.

Maintained by Timothy Beechey. Last updated 10 months ago.

classificationdata-analysispsychology-experimentsrcppstatistical-analysisstatisticsopenblascppopenmp

4.30 score 2 scripts

jm-umn

distfreereg:Distribution-Free Goodness-of-Fit Testing for Regression

Implements distribution-free goodness-of-fit regression testing for the mean structure of parametric models introduced in Khmaladze (2021) <doi:10.1007/s10463-021-00786-3>.

Maintained by Jesse Miller. Last updated 4 months ago.

4.25 score 178 scripts

quantsch

Strategy:Generic Framework to Analyze Trading Strategies

Users can build and test customized quantitative trading strategies. Some quantitative trading strategies are already implemented, e.g. various moving-average filters with trend following approaches. The implemented class called "Strategy" allows users to access several methods to analyze performance figures, plots and backtest the strategies. Furthermore, custom strategies can be added, a generic template is available. The custom strategies require a certain input and output so they can be called from the Strategy-constructor.

Maintained by Julian Busch. Last updated 8 years ago.

4.18 score 30 scripts

solarization

solaR2:Radiation and Photovoltaic Systems

Provides tools for calculating solar geometry, solar radiation on horizontal and inclined planes, and simulating the performance of various photovoltaic (PV) systems. Supports daily and intradaily irradiation data, enabling detailed analysis of grid-connected and water-pumping PV systems, including shading effects and solar angle calculations.

Maintained by Francisco Delgado-López. Last updated 1 months ago.

1 stars 4.08 score 5 scripts

eutwt

versus:Compare Data Frames

A toolset for interactively exploring the differences between two data frames.

Maintained by Ryan Dickerson. Last updated 9 months ago.

7 stars 4.02 score 4 scripts

kim0sun

slca:Structural Modeling for Multiple Latent Class Variables

Provides comprehensive tools for the implementation of Structural Latent Class Models (SLCM), including Latent Transition Analysis (LTA; Linda M. Collins and Stephanie T. Lanza, 2009) <doi:10.1002/9780470567333>, Latent Class Profile Analysis (LCPA; Hwan Chung et al., 2010) <doi:10.1111/j.1467-985x.2010.00674.x>, and Joint Latent Class Analysis (JLCA; Saebom Jeon et al., 2017) <doi:10.1080/10705511.2017.1340844>, and any other extended models involving multiple latent class variables.

Maintained by Youngsun Kim. Last updated 3 months ago.

cpp

3.90 score 5 scripts

hanel

musica:Multiscale Climate Model Assessment

Provides functions allowing for (1) easy aggregation of multivariate time series into custom time scales, (2) comparison of statistical summaries between different data sets at multiple time scales (e.g. observed and bias-corrected data), (3) comparison of relations between variables and/or different data sets at multiple time scales (e.g. correlation of precipitation and temperature in control and scenario simulation) and (4) transformation of time series at custom time scales.

Maintained by Martin Hanel. Last updated 8 years ago.

3.85 score 14 scripts

alekrutkowski

eurodata:Fast and Easy Eurostat Data Import and Search

Interface to Eurostat’s API (SDMX 2.1) with fast data.table-based import of data, labels, and metadata. On top of the core functionality, data search and data description/comparison functions are also provided. Use <https://github.com/alekrutkowski/eurodata_codegen> — a point-and-click app for rapid and easy generation of richly-commented R code — to import a Eurostat dataset or its subset (based on the eurodata::importData() function).

Maintained by Aleksander Rutkowski. Last updated 4 months ago.

cpp

11 stars 3.74 score 7 scripts

mdbrown

TreatmentSelection:Evaluate Treatment Selection Biomarkers

A suite of descriptive and inferential methods designed to evaluate one or more biomarkers for their ability to guide patient treatment recommendations. Package includes functions to assess the calibration of risk models; and plot, evaluate, and compare markers. Please see the reference Janes H, Brown MD, Huang Y, et al. (2014) <doi:10.1515/ijb-2012-0052> for further details.

Maintained by Marshall Brown. Last updated 8 years ago.

3 stars 3.62 score 14 scripts

cran

randomizeR:Randomization for Clinical Trials

This tool enables the user to choose a randomization procedure based on sound scientific criteria. It comprises the generation of randomization sequences as well the assessment of randomization procedures based on carefully selected criteria. Furthermore, 'randomizeR' provides a function for the comparison of randomization procedures.

Maintained by Ralf-Dieter Hilgers. Last updated 2 years ago.

2 stars 3.38 score 1 dependents

mabe0033

MSCMT:Multivariate Synthetic Control Method Using Time Series

Three generalizations of the synthetic control method (which has already an implementation in package 'Synth') are implemented: first, 'MSCMT' allows for using multiple outcome variables, second, time series can be supplied as economic predictors, and third, a well-defined cross-validation approach can be used. Much effort has been taken to make the implementation as stable as possible (including edge cases) without losing computational efficiency. A detailed description of the main algorithms is given in Becker and Klößner (2018) <doi:10.1016/j.ecosta.2017.08.002>.

Maintained by Martin Becker. Last updated 1 years ago.

fortranopenblas

2 stars 3.32 score 35 scripts

phamdn

mbRes:Exploration of Multiple Biomarker Responses using Effect Size

Summarize multiple biomarker responses of aquatic organisms to contaminants using Cliff’s delta, as described in Pham & Sokolova (2023) <doi:10.1002/ieam.4676>.

Maintained by Duy Nghia Pham. Last updated 7 months ago.

3.00 score 1 scripts

rueda-lab

iC10:A Copy Number and Expression-Based Classifier for Breast Tumours

Implementation of the classifier described in the paper Ali HR et al (2014) <doi:10.1186/s13059-014-0431-1>. It uses copy number and/or expression form breast cancer data, trains a Tibshirani's 'pamr' classifier with the features available and predicts the iC10 group.

Maintained by Oscar M Rueda. Last updated 8 months ago.

2.94 score 12 scripts 4 dependents

oscarperpinan

solaR:Radiation and Photovoltaic Systems

Calculation methods of solar radiation and performance of photovoltaic systems from daily and intradaily irradiation data sources.

Maintained by Oscar Perpiñán Lamigueiro. Last updated 3 years ago.

1 stars 2.74 score 55 scripts

pll21

pKSEA:Prediction-Based Kinase-Substrate Enrichment Analysis

A tool for inferring kinase activity changes from phosphoproteomics data. 'pKSEA' uses kinase-substrate prediction scores to weight observed changes in phosphopeptide abundance to calculate a phosphopeptide-level contribution score, then sums up these contribution scores by kinase to obtain a phosphoproteome-level kinase activity change score (KAC score). 'pKSEA' then assesses the significance of changes in predicted substrate abundances for each kinase using permutation testing. This results in a permutation score (pKSEA significance score) reflecting the likelihood of a similarly high or low KAC from random chance, which can then be interpreted in an analogous manner to an empirically calculated p-value. 'pKSEA' contains default databases of kinase-substrate predictions from 'NetworKIN' (NetworKINPred_db) <http://networkin.info> Horn, et. al (2014) <doi:10.1038/nmeth.2968> and of known kinase-substrate links from 'PhosphoSitePlus' (KSEAdb) <https://www.phosphosite.org/> Hornbeck PV, et. al (2015) <doi:10.1093/nar/gku1267>.

Maintained by Peter Liao. Last updated 7 years ago.

2.70 score 8 scripts

zchmielewska

actuaryr:Develop Actuarial Models

Actuarial reports are prepared for the last day of a specific period, such as a month, a quarter or a year. Actuarial models assume that certain events happen at the beginning or end of periods. The package contains functions to easily refer to the first or last (working) day within a specific period relative to a base date to facilitate actuarial reporting and to compare results.

Maintained by Zuzanna Chmielewska. Last updated 5 years ago.

2.70 score 4 scripts

ugroempi

DoE.wrapper:Wrapper Package for Design of Experiments Functionality

Various kinds of designs for (industrial) experiments can be created. The package uses, and sometimes enhances, design generation routines from other packages. So far, response surface designs from package 'rsm', Latin hypercube samples from packages 'lhs' and 'DiceDesign', and D-optimal designs from package 'AlgDesign' have been implemented.

Maintained by Ulrike Groemping. Last updated 2 years ago.

2.45 score 27 scripts 2 dependents

yangfengstat

nproc:Neyman-Pearson (NP) Classification Algorithms and NP Receiver Operating Characteristic (NP-ROC) Curves

In many binary classification applications, such as disease diagnosis and spam detection, practitioners commonly face the need to limit type I error (i.e., the conditional probability of misclassifying a class 0 observation as class 1) so that it remains below a desired threshold. To address this need, the Neyman-Pearson (NP) classification paradigm is a natural choice; it minimizes type II error (i.e., the conditional probability of misclassifying a class 1 observation as class 0) while enforcing an upper bound, alpha, on the type I error. Although the NP paradigm has a century-long history in hypothesis testing, it has not been well recognized and implemented in classification schemes. Common practices that directly limit the empirical type I error to no more than alpha do not satisfy the type I error control objective because the resulting classifiers are still likely to have type I errors much larger than alpha. As a result, the NP paradigm has not been properly implemented for many classification scenarios in practice. In this work, we develop the first umbrella algorithm that implements the NP paradigm for all scoring-type classification methods, including popular methods such as logistic regression, support vector machines and random forests. Powered by this umbrella algorithm, we propose a novel graphical tool for NP classification methods: NP receiver operating characteristic (NP-ROC) bands, motivated by the popular receiver operating characteristic (ROC) curves. NP-ROC bands will help choose in a data adaptive way and compare different NP classifiers.

Maintained by Yang Feng. Last updated 5 years ago.

2.23 score 17 scripts

tathey

VLF:Frequency Matrix Approach for Assessing Very Low Frequency Variants in Sequence Records

Using frequency matrices, very low frequency variants (VLFs) are assessed for amino acid and nucleotide sequences. The VLFs are then compared to see if they occur in only one member of a species, singleton VLFs, or if they occur in multiple members of a species, shared VLFs. The amino acid and nucleotide VLFs are then compared to see if they are concordant with one another. Amino acid VLFs are also assessed to determine if they lead to a change in amino acid residue type, and potential changes to protein structures. Based on Stoeckle and Kerr (2012) <doi:10.1371/journal.pone.0043992>.

Maintained by Taryn B. T. Athey. Last updated 3 years ago.

2.16 score 48 scripts 1 dependents

syerramilli

sysid:System Identification in R

Provides functions for constructing mathematical models of dynamical systems from measured input-output data.

Maintained by Suraj Yerramilli. Last updated 8 years ago.

2.08 score 24 scripts

cran

packHV:A few Useful Functions for Statisticians

Various useful functions for statisticians: describe data, plot Kaplan-Meier curves with numbers of subjects at risk, compare data sets, display spaghetti-plot, build multi-contingency tables...

Maintained by Hugo Varet. Last updated 6 days ago.

1.70 score

blansche

fdm2id:Data Mining and R Programming for Beginners

Contains functions to simplify the use of data mining methods (classification, regression, clustering, etc.), for students and beginners in R programming. Various R packages are used and wrappers are built around the main functions, to standardize the use of data mining methods (input/output): it brings a certain loss of flexibility, but also a gain of simplicity. The package name came from the French "Fouille de Données en Master 2 Informatique Décisionnelle".

Maintained by Alexandre Blansché. Last updated 2 years ago.

1 stars 1.62 score 42 scripts

mousieur-g

ed50:Estimate ED50 and Its Confidence Interval

Functions of five estimation method for ED50 (50 percent effective dose) are provided, and they are respectively Dixon-Mood method (1948) <doi:10.2307/2280071>, Choi's original turning point method (1990) <doi:10.2307/2531453> and it's modified version given by us, as well as logistic regression and isotonic regression. Besides, the package also supports comparison between two estimation results.

Maintained by Yongbo Gan. Last updated 6 years ago.

1.34 score 22 scripts

raulwangfr

ed50simulation:Estimate ED50 and Its Confidence Interval

Functions of five estimation method for ED50 (50 percent effective dose) are provided, and they are respectively Dixon-Mood method (1948) <doi:10.2307/2280071>, Choi's original turning point method (1990) <doi:10.2307/2531453> and it's modified version given by us, as well as logistic regression and isotonic regression. Besides, the package also supports comparison between two estimation results.

Maintained by Fengru Wang. Last updated 5 years ago.

1.18 score 15 scripts

cran

matman:Material Management

A set of functions, classes and methods for performing ABC and ABC/XYZ analyses, identifying overperforming, underperforming and constantly performing items, and plotting, analyzing as well as predicting the temporal development of items.

Maintained by Leon Binder. Last updated 3 years ago.

1.00 score

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