gllvm (version 2.0.5)

getResidualCor.gllvm: Extract residual correlations from gllvm object

Description

Calculates the residual correlation matrix for gllvm model.

Usage

# S3 method for gllvm
getResidualCor(object, adjust = 1, x = NULL, ...)

Arguments

object

an object of class 'gllvm'.

adjust

The type of adjustment used for negative binomial and binomial distribution when computing residual correlation matrix. Options are 0 (no adjustment), 1 (the default adjustment) and 2 (alternative adjustment for NB distribution). See details.

x

(optional) vector of covariate values to calculate the covariance for, when applicable.

...

not used

Author

Francis K.C. Hui, Jenni Niku, David I. Warton

Details

Residual correlation matrix is calculated based on the residual covariance matrix, see details from getResidualCov.gllvm.

Examples

#'# Extract subset of the microbial data to be used as an example
data(microbialdata)
y <- microbialdata$Y[, order(colMeans(microbialdata$Y > 0), 
                     decreasing = TRUE)[21:40]]
fit <- gllvm(y, family = poisson())
fit$logL
cr <- getResidualCor(fit)
cr[1:5,1:5]
if (FALSE) {
# Load a dataset from the mvabund package
data(antTraits, package = "mvabund")
y <- as.matrix(antTraits$abund)
# Fit gllvm model
fit <- gllvm(y = y, family = poisson())
# residual correlations:
cr <- getResidualCor(fit)
# Plot residual correlations:
install.packages("corrplot", "gclus")
library(corrplot)
library(gclus)
corrplot(cr[order.single(cr), order.single(cr)], diag = F,
  type = "lower", method = "square", tl.cex = 0.8, tl.srt = 45, tl.col = "red")
  }