DHARMa-package: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level /...
In DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models
DHARMa-package R Documentation
DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models
Description
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.
Details
To get started with the package, look at the vignette and start with simulateResiduals
Author(s)
Maintainer: Florian Hartig florian.hartig@biologie.uni-regensburg.de (ORCID)
Other contributors:
Lukas Lohse [contributor]
Melina de Souza leite [contributor]
References
vignette("DHARMa", package="DHARMa")
See Also
Useful links:
DHARMa documentation built on Oct. 18, 2024, 5:09 p.m.
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| DHARMa-package | R Documentation |
DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models
Description
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.
Details
To get started with the package, look at the vignette and start with simulateResiduals
Author(s)
Maintainer: Florian Hartig florian.hartig@biologie.uni-regensburg.de (ORCID)
Other contributors:
Lukas Lohse [contributor]
Melina de Souza leite [contributor]
References
vignette("DHARMa", package="DHARMa")
See Also
Useful links:
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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