clpca: Cumulative Logistic (Restricted) PCA

In lmap: Logistic Mapping

Cumulative Logistic (Restricted) PCA

Description

Cumulative Logistic (Restricted) PCA

Usage

clpca(
  Y,
  X = NULL,
  S = 2,
  start = NULL,
  lambda = FALSE,
  trace = FALSE,
  maxiter = 65536,
  dcrit = 1e-06
)

Arguments

Y	An N times R ordinal matrix .
X	An N by P matrix with predictor variables
S	Positive number indicating the dimensionality of the solution
start	Starting values for U or B and V
lambda	if TRUE does lambda scaling (see Understanding Biplots, p24)
trace	tracing information during iterations
maxiter	maximum number of iterations
dcrit	convergence criterion

Value

Y Matrix Y from input

Xoriginal Matrix X from input

X Scaled X matrix

mx Mean values of X

sdx Standard deviations of X

ynames Variable names of responses

xnames Variable names of predictors

probabilities Estimated values of Y

m main effects

U matrix with coordinates for row-objects

B matrix with regression weight (U = XB)

V matrix with vectors for items/responses

iter number of main iterations from the MM algorithm

deviance value of the deviance at convergence

Examples

## Not run: 
data(dataExample_clpca)
Y<-as.matrix(dataExample_clpca[,5:8])
X<-as.matrix(dataExample_clpca[,1:4])
out = clpca(Y)
out = clpca(Y, X)

## End(Not run)

lmap documentation built on April 3, 2025, 5:47 p.m.