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."


Reference manual

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install.packages("DHARMa")

0.5.0 by Florian Hartig, 5 months ago


http://florianhartig.github.io/DHARMa/


Report a bug at https://github.com/florianhartig/DHARMa/issues


Browse source code at https://github.com/cran/DHARMa


Authors: Florian Hartig [aut, cre] (ORCID: , Lukas Lohse [ctb] , Melina de Souza Leite [ctb] (ORCID: , Cosmina Werneke [ctb]


Documentation:   PDF Manual  


GPL (>= 3) license


Imports stats, graphics, utils, grDevices, Matrix, parallel, gap, lmtest, ape, qgam, lme4

Suggests knitr, testthat, rmarkdown, KernSmooth, sfsmisc, MASS, mgcv, mgcViz, spaMM, GLMMadaptive, glmmTMB, phylolm, brms

Enhances rstan, phyr, rjags, BayesianTools


Imported by AssumpSure, BayesianTools, RMeDPower2, bizicount, eDITH, ecoGLMM, insurancerating, regressinator, rfriend.

Suggested by GLMMadaptive, GLMMcosinor, dsem, easystats, ecostats, ewp, gdpar, glmmTMB, gp3tools, iop, lme4, performance, phyr, qbrms, qra, sdmTMB, see, seqwrap, tinyVAST, underdisp.


See at CRAN