lmap (version 0.2.4)

mru: Multinomial Restricted MDU

Description

The function mru performs multinomial restricted unfolding for a nominal response variable and a set of predictor variables.

Usage

mru(y, X, Z = NULL, S = 2, start = "da", maxiter = 65536, dcrit = 1e-06)

Value

Y Matrix Y from input

Xoriginal Matrix X from input

X Scaled X matrix

G class indicator matrix

ynames class names of response variable

xnames variable names of the predictors

mx means of the predictor variables

sdx standard deviations of the predictor variables

U coordinate matrix of row objects

B matrix with regression coefficients

V Class coordinate matrix

iters number of iterations

deviance value of the deviance at convergence

Arguments

y

An N vector of the responses (categorical) or an indicator matrix of size N x C (obligatory when Z is used)

X

An N by P matrix with predictor variables

Z

Design matrix for the class points (V)

S

Positive number indicating the dimensionality of the solution

start

Type of starting values (da: discriminant analysis, random or list with B and V)

maxiter

maximum number of iterations

dcrit

convergence criterion

Examples

if (FALSE) {
data(dataExample_mru)
y = as.matrix(dataExample_mru[ , 1])
X = as.matrix(dataExample_mru[ , 2:6])
output = mru(y = y, X = X, S = 2)
}