benchmarkRuntime {DHARMa} | R Documentation |
Benchmark runtimes of several functions
Description
Benchmark runtimes of several functions
Usage
benchmarkRuntime(createModel, evaluationFunctions, n)
Arguments
createModel |
a function that creates and returns a fitted model |
evaluationFunctions |
a list of functions that are to be evaluated on the fitted models |
n |
number of replicates |
Details
This is a small helper function designed to benchmark runtimes of several operations that are to be performed on a list of fitted models. In the example, this is used to benchmark the runtimes of several DHARMa tests
Author(s)
Florian Hartig
Examples
createModel = function(){
testData = createData(family = poisson(), overdispersion = 1,
randomEffectVariance = 0)
fittedModel <- glm(observedResponse ~ Environment1, data = testData, family = poisson())
return(fittedModel)
}
a = function(m){
testUniformity(m, plot = FALSE)$p.value
}
b = function(m){
testDispersion(m, plot = FALSE)$p.value
}
c = function(m){
testDispersion(m, plot = FALSE, type = "PearsonChisq")$p.value
}
evaluationFunctions = list(a,b, c)
benchmarkRuntime(createModel, evaluationFunctions, 2)
[Package DHARMa version 0.4.6 Index]