Reference

All functions
AICc(<gllvm>) nobs(<gllvm>)	Corrected Akaike information criterion and number of observations
anova(<gllvm>)	Analysis Of Deviance for gllvm
beetle	ground beetle assemblages
coefplot(<gllvm>)	Plot covariate coefficients and confidence intervals
confint(<gllvm>)	Confidence intervals for model parameters
optima(<gllvm>) tolerances(<gllvm>)	Functions to extract ecological quantities of the latent variables from a GLLVM, if species are a quadratic function of the latent variables.
eSpider	Hunting spider data
fungi	Wood-decaying fungi data
getEnvironCov(<gllvm>)	Extract species covariances due to environmental random effects from gllvm object
getLoadings(<gllvm>)	Extract loadings
getLV(<gllvm>)	Extract latent variables
getPredictErr(<gllvm>)	Extract prediction errors for latent variables from gllvm object
getResidualCor(<gllvm>)	Extract residual correlations from gllvm object
getResidualCov(<gllvm>)	Extract residual covariance matrix from gllvm object
gllvm()	Generalized Linear Latent Variable Models
goodnessOfFit()	Goodness of fit measures for a gllvm
kelpforest	Kelp Forest community Dynamics: Cover of sessile organisms, Uniform Point Contact
logLik(<gllvm>)	Log-likelihood of gllvm
microbialdata	Microbial community data
ordiplot(<gllvm>)	Plot latent variables from gllvm model
phyloplot(<gllvm>)	Plot phylogenetic random effects from gllvm
plot(<gllvm>)	Plot Diagnostics for an gllvm Object
predict(<gllvm>)	Predict Method for gllvm Fits
predictLVs(<gllvm>)	Predict latent variables for gllvm Fits
randomCoefplot(<gllvm>)	Plot random slope coefficients
residuals(<gllvm>)	Dunn-Smyth residuals for gllvm model
se(<gllvm>)	Standard errors for gllvm model
simulate(<gllvm>)	Simulate data from gllvm fit
Skabbholmen	Skabbholmen island data
summary(<gllvm>) print(<summary.gllvm>) plot(<summary.gllvm>)	Summarizing gllvm model fits
update(<gllvm>)	Update and Re-fit a gllvm Model Call
vcov(<gllvm>)	Returns variance-covariance matrix of coefficients in a GLLVM.
VP(<gllvm>) print(<VP.gllvm>) plotVarPartitioning() plotVP() plot(<VP.gllvm>)	Calculate variance partitioning