DHARMa (version 0.4.7)

testPhylogeneticAutocorrelation: Test for phylogenetic autocorrelation

Description

This function performs a Moran's I test for phylogenetic autocorrelation on the calculated quantile residuals.

Usage

testPhylogeneticAutocorrelation(simulationOutput, tree,
  alternative = c("two.sided", "greater", "less"))

Arguments

simulationOutput

an object of class DHARMa, either created via simulateResiduals for supported models or via 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.

tree

A phylogenetic tree object.

alternative

A character string specifying whether the test should test if observations are "greater", "less" or "two.sided" compared to the simulated null hypothesis of no phylogenetic correlation.

Author

Florian Hartig

Details

The function performs Moran.I test from the package ape on the DHARMa residuals, based on the phylogenetic distance matrix internally created from the provided tree. For custom distance matrices, you can use testSpatialAutocorrelation.

See Also

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

Examples

if (FALSE) {

  library(DHARMa)
  library(phylolm)

  set.seed(123)
  tre = rcoal(60)
  b0 = 0; b1 = 1;
  x <- runif(length(tre$tip.label), 0, 1)
  y <- b0 + b1*x +
    rTrait(n = 1, phy = tre,model="BM",
           parameters = list(ancestral.state = 0, sigma2 = 10))
  dat = data.frame(trait = y, pred = x)

  fit = lm(trait ~ pred, data = dat)
  res = simulateResiduals(fit, plot = T)

  testPhylogeneticAutocorrelation(res, tree = tre)


  fit = phylolm(trait ~ pred, data = dat, phy = tre, model = "BM")
  summary(fit)

  # phylogenetic autocorrelation still present in residuals
  res = simulateResiduals(fit, plot = T)

  # with "rotation" the residual autcorrelation is gone, see ?simulateResiduals.
  res = simulateResiduals(fit, plot = T, rotation = "estimated")

}