testResiduals: DHARMa general residual test

View source: R/tests.R

testResidualsR Documentation

DHARMa general residual test


Calls both uniformity and dispersion test


testResiduals(simulationOutput, plot = T)



an object of class DHARMa, either created via simulateResiduals for supported models or by createDHARMa for simulations created outside DHARMa, or a supported model. Providing a supported model directly is discouraged, because simulation settings cannot be changed in this case.


if T, plots functions of the tests are called


This function is a wrapper for the various test functions implemented in DHARMa. Currently, this function calls the testUniformity and the testDispersion functions. All other tests (see list below) have to be called by hand.


Florian Hartig

See Also

testResiduals, testUniformity, testOutliers, testDispersion, testZeroInflation, testGeneric, testTemporalAutocorrelation, testSpatialAutocorrelation, testQuantiles, testCategorical


testData = createData(sampleSize = 100, overdispersion = 0.5, randomEffectVariance = 0)
fittedModel <- glm(observedResponse ~ Environment1 , family = "poisson", data = testData)
simulationOutput <- simulateResiduals(fittedModel = fittedModel)

# the plot function runs 4 tests
# i) KS test i) Dispersion test iii) Outlier test iv) quantile test
plot(simulationOutput, quantreg = TRUE)

# testResiduals tests distribution, dispersion and outliers
# testResiduals(simulationOutput)

####### Individual tests #######

# KS test for correct distribution of residuals

# KS test for correct distribution within and between groups
testCategorical(simulationOutput, testData$group)

# Dispersion test - for details see ?testDispersion
testDispersion(simulationOutput) # tests under and overdispersion

# Outlier test (number of observations outside simulation envelope)
# Use type = "boostrap" for exact values, see ?testOutliers
testOutliers(simulationOutput, type = "binomial")

# testing zero inflation

# testing generic summaries
countOnes <- function(x) sum(x == 1)  # testing for number of 1s
testGeneric(simulationOutput, summary = countOnes) # 1-inflation
testGeneric(simulationOutput, summary = countOnes, alternative = "less") # 1-deficit

means <- function(x) mean(x) # testing if mean prediction fits
testGeneric(simulationOutput, summary = means)

spread <- function(x) sd(x) # testing if mean sd fits
testGeneric(simulationOutput, summary = spread)

DHARMa documentation built on Sept. 9, 2022, 1:06 a.m.