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glmmTMB - Generalized Linear Mixed Models using Template Model Builder

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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cppopenmp

17.65 score 366 stars 38 dependents 7.5k scripts 56k downloads

brms - Bayesian Regression Models using 'Stan'

Fit Bayesian generalized (non-)linear multivariate multilevel models using 'Stan' for full Bayesian inference. A wide range of distributions and link functions are supported, allowing users to fit -- among others -- linear, robust linear, count data, survival, response times, ordinal, zero-inflated, hurdle, and even self-defined mixture models all in a multilevel context. Further modeling options include both theory-driven and data-driven non-linear terms, auto-correlation structures, censoring and truncation, meta-analytic standard errors, and quite a few more. In addition, all parameters of the response distribution can be predicted in order to perform distributional regression. Prior specifications are flexible and explicitly encourage users to apply prior distributions that actually reflect their prior knowledge. Models can easily be evaluated and compared using several methods assessing posterior or prior predictions. References: Bürkner (2017) <doi:10.18637/jss.v080.i01>; Bürkner (2018) <doi:10.32614/RJ-2018-017>; Bürkner (2021) <doi:10.18637/jss.v100.i05>; Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>.

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bayesian-inferencebrmsmultilevel-modelsstanstatistical-models

17.10 score 1.4k stars 41 dependents 23k scripts 41k downloads

DHARMa - Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models

"Uses a simulation-based approach to create readily interpretable scaled (quantile) residuals for fitted generalized linear (mixed) models. Currently supported are linear and generalized linear (mixed) models from 'lme4' (classes 'lmerMod', 'glmerMod'), 'glmmTMB', 'GLMMadaptive', 'spaMM', and 'brms' (simple models); phylogenetic linear models from 'phylolm' (classes 'phylolm' and 'phyloglm'); generalized additive models ('gam' from 'mgcv'); 'glm' (including 'negbin' from 'MASS', but excluding quasi-distributions) and 'lm' model classes. Moreover, externally created simulations, e.g. posterior predictive simulations from Bayesian software such as 'JAGS', 'STAN', or 'BUGS' can be processed as well. The resulting residuals are standardized to values between 0 and 1 and can be interpreted as intuitively as residuals from a linear regression. The package also provides a number of plot and test functions for typical model misspecification problems, such as over/underdispersion, zero-inflation, and residual spatial, temporal and phylogenetic autocorrelation."

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glmmregressionregression-diagnosticsresidual

15.63 score 259 stars 19 dependents 4.4k scripts 28k downloads

openssl - Toolkit for Encryption, Signatures and Certificates Based on OpenSSL

Bindings to OpenSSL libssl and libcrypto, plus custom SSH key parsers. Supports RSA, DSA and EC curves P-256, P-384, P-521, and curve25519. Cryptographic signatures can either be created and verified manually or via x509 certificates. AES can be used in cbc, ctr or gcm mode for symmetric encryption; RSA for asymmetric (public key) encryption or EC for Diffie Hellman. High-level envelope functions combine RSA and AES for encrypting arbitrary sized data. Other utilities include key generators, hash functions (md5, sha1, sha256, etc), base64 encoder, a secure random number generator, and 'bignum' math methods for manually performing crypto calculations on large multibyte integers.

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openssl

13.20 score 5.1k dependents 798 scripts 931k downloads

mgcv - Mixed GAM Computation Vehicle with Automatic Smoothness Estimation

Generalized additive (mixed) models, some of their extensions and other generalized ridge regression with multiple smoothing parameter estimation by (Restricted) Marginal Likelihood, Cross Validation and similar, or using iterated nested Laplace approximation for fully Bayesian inference. See Wood (2025) <doi:10.1146/annurev-statistics-112723-034249> for an overview. Includes a gam() function, a wide variety of smoothers, 'JAGS' support and distributions beyond the exponential family.

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openblasopenmp

12.75 score 34 stars 2.4k dependents 25k scripts 91k downloads

logistf - Firth's Bias-Reduced Logistic Regression

Fit a logistic regression model using Firth's bias reduction method, equivalent to penalization of the log-likelihood by the Jeffreys prior. Confidence intervals for regression coefficients can be computed by penalized profile likelihood. Firth's method was proposed as ideal solution to the problem of separation in logistic regression, see Heinze and Schemper (2002) <doi:10.1002/sim.1047>. If needed, the bias reduction can be turned off such that ordinary maximum likelihood logistic regression is obtained. Two new modifications of Firth's method, FLIC and FLAC, lead to unbiased predictions and are now available in the package as well, see Puhr et al (2017) <doi:10.1002/sim.7273>.

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openblas

10.03 score 15 stars 18 dependents 654 scripts 20k downloads

ordbetareg - Ordered Beta Regression Models with 'brms'

Implements ordered beta regression models, which are for modeling continuous variables with upper and lower bounds, such as survey sliders, dose-response relationships and indexes. For more information, see Kubinec (2023) <doi:10.31235/osf.io/2sx6y>. The package is a front-end to the R package 'brms', which facilitates a range of regression specifications, including hierarchical, dynamic and multivariate modeling.

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quarto

7.64 score 21 stars 1 dependents 92 scripts 5.0k downloads

roomba - Tidy up nested list hairballs

This is a package to transform large, multi-nested lists into a more user-friendly format. The initial focus is on making processing of return values from `jsonlite::fromJSON()` queries more seamless, but ideally this package should be useful for deeply-nested lists from an array of sources.

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unconfunconf18

6.63 score 136 stars 1 dependents 35 scripts

x13binary - Provide the 'x13ashtml' Seasonal Adjustment Binary

The US Census Bureau provides a seasonal adjustment program now called 'X-13ARIMA-SEATS' building on both earlier programs called X-11 and X-12 as well as the SEATS program by the Bank of Spain. The US Census Bureau offers both source and binary versions -- which this package integrates for use by other R packages.

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5.21 score 7 dependents 19 scripts 13k downloads

rethinking - Statistical Rethinking book package

Utilities for fitting and comparing models

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5.00 score 5.0k scripts

collostructions - An R Implementation for the Family of Collostructional Methods

Functions and example data for collostructional or collocational analyses.

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2.79 score 62 scripts

ggforestplot - Forestplots of Measures of Effects and Their Confidence Intervals

A collection of functions, based on ggplot2, to plot forestplots of measures of effects, e.g. linear associations, with their confidence intervals.

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6.42 score 65 stars 407 scripts

mmtable2 - Create and combine tables with a ggplot2/patchwork syntax

Add headers using data from a column in your data frame. Combine tables with +, / and * operators. Output tables in gt package format.

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6.34 score 128 stars 68 scripts

tjmisc - TJ's Miscellany

A collection of helper functions.

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2.70 score 10 stars 5 scripts

huttenlocher1991 - Vocabulary growth in 22 infants (Huttenlocher et al., 1991)

Provides vocabulary growth dataset from Huttenlocher et al. (1991) <https://doi.org/10.1037/0012-1649.27.2.236>. This dataset is useful educationally because it features longitudinal/repeated measures growth data. It is also unusual because the only fixed effect predictor is quadratic time--that is, there is no intercept or linear time terms.

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1.70 score 2 scripts