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DHARMa (version 0.4.7)

residuals.DHARMa: Return residuals of a DHARMa simulation

Description

Return residuals of a DHARMa simulation

Usage

# S3 method for DHARMa
residuals(object, quantileFunction = NULL,
  outlierValues = NULL, ...)

Arguments

object

an object with simulated residuals created by simulateResiduals

quantileFunction

optional - a quantile function to transform the uniform 0/1 scaling of DHARMa to another distribution

outlierValues

if a quantile function with infinite support (such as dnorm) is used, residuals that are 0/1 are mapped to -Inf / Inf. outlierValues allows to convert -Inf / Inf values to an optional min / max value.

...

optional arguments for compatibility with the generic function, no function implemented

Details

the function accesses the slot $scaledResiduals in a fitted DHARMa object, and optionally transforms the standard DHARMa quantile residuals (which have a uniform distribution) to a particular pdf.

Examples

Run this code
library(lme4)

testData = createData(sampleSize = 100, overdispersion = 0.5, family = poisson())
fittedModel <- glmer(observedResponse ~ Environment1 + (1|group), 
                     family = "poisson", data = testData)

simulationOutput <- simulateResiduals(fittedModel = fittedModel)

# standard plot 
plot(simulationOutput)

# one of the possible test, for other options see ?testResiduals / vignette
testDispersion(simulationOutput)

# the calculated residuals can be accessed via 
residuals(simulationOutput)

# transform residuals to other pdf, see ?residuals.DHARMa for details
residuals(simulationOutput, quantileFunction = qnorm, outlierValues = c(-7,7))

# get residuals that are outside the simulation envelope
outliers(simulationOutput)

# calculating aggregated residuals per group
simulationOutput2 = recalculateResiduals(simulationOutput, group = testData$group)
plot(simulationOutput2, quantreg = FALSE)

# calculating residuals only for subset of the data
simulationOutput3 = recalculateResiduals(simulationOutput, sel = testData$group == 1 )
plot(simulationOutput3, quantreg = FALSE)

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