gllvm: predictLVs.gllvm – R documentation

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predictLVs.gllvm

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 <jenni.m.e.niku@jyu.fi>

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

Generalized Linear Latent Variable Models

v1.3.0

GPL-2

Authors

Jenni Niku [aut, cre], Wesley Brooks [aut], Riki Herliansyah [aut], Francis K.C. Hui [aut], Sara Taskinen [aut], David I. Warton [aut], Bert van der Veen [aut]

Initial release

2021-4-26