View source: R/getResidualCor.gllvm.R
getResidualCor.gllvm | R Documentation |
Calculates the residual correlation matrix for gllvm model.
## S3 method for class 'gllvm'
getResidualCor(object, adjust = 1, site.index = NULL, ...)
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. |
site.index |
A site index used used in the calculation of a GLLVM with quadratic response model, for which the residual correlations are calculated. |
... |
not used |
Residual correlation matrix is calculated based on the residual covariance matrix, see details from getResidualCov.gllvm
.
Francis K.C. Hui, Jenni Niku, David I. Warton
#'# 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$logL
cr <- getResidualCor(fit)
cr[1:5,1:5]
## Not run:
# Load a dataset from the mvabund package
data(antTraits)
y <- as.matrix(antTraits$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")
## End(Not run)
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