testOverdispersionParametric

<p>a fitted model object. See details for possible models</p>

model

<p>This function implements a parametric dispersion test based on comparing the residual deviance to the residual degrees of freedom that is commonly used, with the purpose of benchmarking against the nonparametric tests of DHARMA</p>

The 'DHARMa' package uses a simulation-based approach to create
readily interpretable scaled (quantile) residuals for fitted generalized linear mixed
models. Currently supported are generalized linear mixed models from 'lme4'
(classes 'lmerMod', 'glmerMod'), generalized additive models ('gam' from 'mgcv'),
'glm' (including 'negbin' from 'MASS', but excluding quasi-distributions) and 'lm' model
classes. Alternatively, 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 and temporal autocorrelation.

Florian Hartig

testOverdispersionParametric: Parametric overdispersion test

Description

Usage

Arguments

Details

See Also