testUniformity

a DHARMa object with simulated residuals created with <code><a rd-options="" href="/link/simulateResiduals?package=DHARMa&version=0.2.2" data-mini-rdoc="DHARMa::simulateResiduals">simulateResiduals</a></code>

simulationOutput

a character string specifying whether the test should test if observations are "greater", "less" or "two.sided" compared to the simulated null hypothesis. See <code><a rd-options="stats" href="/link/ks.test?package=DHARMa&version=0.2.2&to=stats" data-mini-rdoc="stats::ks.test">ks.test</a></code> for details

alternative

if T, plots calls <code><a rd-options="" href="/link/plotQQunif?package=DHARMa&version=0.2.2" data-mini-rdoc="DHARMa::plotQQunif">plotQQunif</a></code> as well

plot

This function tests the overall uniformity of the simulated residuals in a DHARMa object

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'), 'glmmTMB' and 'spaMM', 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 and temporal autocorrelation.

Florian Hartig

DHARMa

Residual Diagnostics for Hierarchical (Multi-Level / Mixed)
Regression Models

testUniformity function

a DHARMa object with simulated residuals created with <code><a rd-options='' href='simulateResiduals'>simulateResiduals</a></code>

a character string specifying whether the test should test if observations are "greater", "less" or "two.sided" compared to the simulated null hypothesis. See <code><a rd-options='stats' href='ks.test'>ks.test</a></code> for details

if T, plots calls <code><a rd-options='' href='plotQQunif'>plotQQunif</a></code> as well

testUniformity: Test for overall uniformity

Description

Usage

Arguments

Details

See Also