do3PCA (version 1.0.0)

ProbPCA: Probabilistic PCA

Description

Function to perform (non-phylogenetic) probabilistic PCA. This function is a modification (fork) of Rdimtools::do.ppca .

Usage

ProbPCA(x, ret_dim = 2)

Value

returns a list of class "phylPPCA". See "Details" for more information.

Arguments

x

a matrix with traits in columns and observations in rows.

ret_dim

number of dimensions (PC axes) to be kept by the model.

Details

This function uses the same algorithm as Rdimtools::do.ppca. However, it returns more details from the estimation and computes AIC and AICc.

The function returns a list with the following elements. scores: the scores of the principal components; projection: the eigenvectors; sig: the MLE of the error of the model; mle.W: the MLE of the W matrix: varnames: the names of the traits; loglik: the log-likelihood of the estimate. Function also returns AIC, AICc, and BIC for the model.

References

Tipping, M. E., and C. M. Bishop. 1999. Probabilistic Principal Component Analysis. Journal of the Royal Statistical Society Series B: Statistical Methodology 61(3):611–622. doi: 10.1111/1467-9868.00196

Examples

dt <- as.matrix( ratematrix::anoles$data[,1:3] )
ppca <- ProbPCA(x = dt, ret_dim = 2)
doBiplot(x = ppca, add_margin = 0.3)