predictLVs.gllvm: Predict latent variables for gllvm Fits

In gllvm: Generalized Linear Latent Variable Models

Predict latent variables for gllvm Fits

Description

Obtains predictions for latent variables from a fitted generalized linear latent variable model object. Currently works only for the variational approximation method.

Usage

## S3 method for class 'gllvm'
predictLVs(object, newX = NULL, newY = object$y, ...)

Arguments

object	an object of class 'gllvm'.
newX	A new data frame of environmental variables. If omitted, the original matrix of environmental variables is used.
newY	A new response data. Defaults to the dataset used for original model fit.
...	not used.

Details

Obtains predictions for latent variables from a fitted generalized linear latent variable model object.

Value

A matrix containing requested predictor types.

Author(s)

David Warton, Jenni Niku <[e-mail]>

Examples

 
# Load a dataset from the mvabund package
data(antTraits)
y <- as.matrix(antTraits$abund)
X <- scale(antTraits$env[, 1:3])
# Fit gllvm model
fit <- gllvm(y = y, X, family = poisson())
# fitted values
predLVs <- predictLVs.gllvm(fit)

gllvm documentation built on Sept. 18, 2023, 5:22 p.m.