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.
Last updated 9 days ago
16.78 score 294 stars 25 packages 3.7k scripts 24k downloadsbrms - 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>.
Last updated 4 days ago
bayesian-inferencebrmsmultilevel-modelsstanstatistical-models
16.49 score 1.3k stars 31 packages 13k scripts 24k downloadsDHARMa - Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models
The 'DHARMa' package 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', and 'spaMM'; 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, phylogenetic and temporal autocorrelation.
Last updated 5 hours ago
glmmregressionregression-diagnosticsresidual
14.70 score 214 stars 9 packages 2.8k scripts 15k downloadsmgcv - 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, Generalized Cross Validation and similar, or using iterated nested Laplace approximation for fully Bayesian inference. See Wood (2017) <doi:10.1201/9781315370279> for an overview. Includes a gam() function, a wide variety of smoothers, 'JAGS' support and distributions beyond the exponential family.
Last updated 11 months ago
12.88 score 31 stars 7.7k packages 17k scripts 63k downloadslogistf - 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>.
Last updated 1 years ago
9.10 score 12 stars 15 packages 316 scripts 7.4k downloadsordbetareg - 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.
Last updated 2 months ago
6.69 score 19 stars 34 scripts 1.3k downloadsroomba - 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.
Last updated 3 years ago
unconfunconf18
6.68 score 138 stars 1 packages 33 scriptsx13binary - 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.
Last updated 22 days ago
5.98 score 10 packages 16 scripts 8.2k downloads
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.
Last updated 3 years ago
6.29 score 130 stars 60 scripts
tjmisc - TJ's Miscellany
A collection of helper functions.
Last updated 2 years ago
2.70 score 10 stars 5 scriptscollostructions - An R Implementation for the Family of Collostructional Methods
Functions and example data for collostructional or collocational analyses.
Last updated 9 months ago
2.23 score 34 scripts