DHARMa
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.
- Version0.4.7
- R version≥ 3.0.2
- LicenseGPL (≥ 3)
- Needs compilation?No
- Last release10/18/2024
Documentation
Team
Florian Hartig
Lukas Lohse
Show author detailsRolesContributorMelina de Souza leite
Show author detailsRolesContributor
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- Depends1 package
- Imports10 packages
- Enhances4 packages
- Suggests12 packages
- Reverse Imports5 packages
- Reverse Suggests11 packages