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r-np
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public |
Nonparametric (and semiparametric) kernel methods that seamlessly handle a mix of continuous, unordered, and ordered factor data types. We would like to gratefully acknowledge support from the Natural Sciences and Engineering Research Council of Canada (NSERC, <http://www.nserc-crsng.gc.ca>), the Social Sciences and Humanities Research Council of Canada (SSHRC, <http://www.sshrc-crsh.gc.ca>), and the Shared Hierarchical Academic Research Computing Network (SHARCNET, <http://www.sharcnet.ca>).
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2025-03-25 |
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r-network
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public |
Tools to create and modify network objects. The network class can represent a range of relational data types, and supports arbitrary vertex/edge/graph attributes.
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2025-03-25 |
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r-mirt
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Analysis of dichotomous and polytomous response data using unidimensional and multidimensional latent trait models under the Item Response Theory paradigm (Chalmers (2012) <doi:10.18637/jss.v048.i06>). Exploratory and confirmatory models can be estimated with quadrature (EM) or stochastic (MHRM) methods. Confirmatory bi-factor and two-tier analyses are available for modeling item testlets. Multiple group analysis and mixed effects designs also are available for detecting differential item and test functioning as well as modeling item and person covariates. Finally, latent class models such as the DINA, DINO, multidimensional latent class, and several other discrete latent variable models, including mixture and zero-inflated response models, are supported.
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2025-03-25 |
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r-mcmcpack
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Contains functions to perform Bayesian inference using posterior simulation for a number of statistical models. Most simulation is done in compiled C++ written in the Scythe Statistical Library Version 1.0.3. All models return 'coda' mcmc objects that can then be summarized using the 'coda' package. Some useful utility functions such as density functions, pseudo-random number generators for statistical distributions, a general purpose Metropolis sampling algorithm, and tools for visualization are provided.
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2025-03-25 |
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r-mboost
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Functional gradient descent algorithm (boosting) for optimizing general risk functions utilizing component-wise (penalised) least squares estimates or regression trees as base-learners for fitting generalized linear, additive and interaction models to potentially high-dimensional data.
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2025-03-25 |
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r-jomo
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Similarly to Schafer's package 'pan', 'jomo' is a package for multilevel joint modelling multiple imputation (Carpenter and Kenward, 2013) <doi: 10.1002/9781119942283>. Novel aspects of 'jomo' are the possibility of handling binary and categorical data through latent normal variables, the option to use cluster-specific covariance matrices and to impute compatibly with the substantive model.
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2025-03-25 |
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r-hipread
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Read hierarchical fixed width files like those commonly used by many census data providers. Also allows for reading of data in chunks, and reading 'gzipped' files without storing the full file in memory.
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2025-03-25 |
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r-gstat
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Variogram modelling; simple, ordinary and universal point or block (co)kriging; spatio-temporal kriging; sequential Gaussian or indicator (co)simulation; variogram and variogram map plotting utility functions; supports sf and stars.
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2025-03-25 |
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r-glmmtmb
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Fit linear and generalized linear mixed models with various extensions, including zero-inflation. The models are fitted using maximum likelihood estimation via 'TMB' (Template Model Builder). Random effects are assumed to be Gaussian on the scale of the linear predictor and are integrated out using the Laplace approximation. Gradients are calculated using automatic differentiation.
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2025-03-25 |
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r-fitar
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Comprehensive model building function for identification, estimation and diagnostic checking for AR and subset AR models. Two types of subset AR models are supported. One family of subset AR models, denoted by ARp, is formed by taking subet of the original AR coefficients and in the other, denoted by ARz, subsets of the partial autocorrelations are used. The main advantage of the ARz model is its applicability to very large order models.
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2025-03-25 |
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r-feather
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public |
Read and write feather files, a lightweight binary columnar data store designed for maximum speed.
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2025-03-25 |
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r-epi
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public |
Functions for demographic and epidemiological analysis in the Lexis diagram, i.e. register and cohort follow-up data, in particular representation, manipulation and simulation of multistate data - the Lexis suite of functions, which includes interfaces to 'mstate', 'etm' and 'cmprsk' packages. Also contains functions for Age-Period-Cohort and Lee-Carter modeling and a function for interval censored data and some useful functions for tabulation and plotting, as well as a number of epidemiological data sets.
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2025-03-25 |
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r-dplyr
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A fast, consistent tool for working with data frame like objects, both in memory and out of memory.
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2025-03-25 |
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r-wordcloud2
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A fast visualization tool for creating wordcloud by using 'wordcloud2.js'. 'wordcloud2.js' is a JavaScript library to create wordle presentation on 2D canvas or HTML <https://timdream.org/wordcloud2.js/>.
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2025-03-25 |
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r-webshot
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Takes screenshots of web pages, including Shiny applications and R Markdown documents.
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2025-03-25 |
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r-webmockr
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Stubbing and setting expectations on 'HTTP' requests. Includes tools for stubbing 'HTTP' requests, including expected request conditions and response conditions. Match on 'HTTP' method, query parameters, request body, headers and more. Can be used for unit tests or outside of a testing context.
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2025-03-25 |
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r-visnetwork
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Provides an R interface to the 'vis.js' JavaScript charting library. It allows an interactive visualization of networks.
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2025-03-25 |
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r-verification
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Utilities for verifying discrete, continuous and probabilistic forecasts, and forecasts expressed as parametric distributions are included.
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2025-03-25 |
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r-vcd
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Visualization techniques, data sets, summary and inference procedures aimed particularly at categorical data. Special emphasis is given to highly extensible grid graphics. The package was package was originally inspired by the book "Visualizing Categorical Data" by Michael Friendly and is now the main support package for a new book, "Discrete Data Analysis with R" by Michael Friendly and David Meyer (2015).
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2025-03-25 |
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r-tsa
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Contains R functions and datasets detailed in the book "Time Series Analysis with Applications in R (second edition)" by Jonathan Cryer and Kung-Sik Chan.
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2025-03-25 |
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r-th.data
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Contains data sets used in other packages Torsten Hothorn maintains.
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2025-03-25 |
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r-tfruns
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Create and manage unique directories for each 'TensorFlow' training run. Provides a unique, time stamped directory for each run along with functions to retrieve the directory of the latest run or latest several runs.
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2025-03-25 |
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r-survey
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public |
Summary statistics, two-sample tests, rank tests, generalised linear models, cumulative link models, Cox models, loglinear models, and general maximum pseudolikelihood estimation for multistage stratified, cluster-sampled, unequally weighted survey samples. Variances by Taylor series linearisation or replicate weights. Post-stratification, calibration, and raking. Two-phase subsampling designs. Graphics. PPS sampling without replacement. Principal components, factor analysis.
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2025-03-25 |
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r-superpc
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Supervised principal components for regression and survival analsysis. Especially useful for high-dimnesional data, including microarray data.
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2025-03-25 |
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r-stubthat
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Create stubs of functions for use while testing.
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2025-03-25 |
