procoteW {lazy.procrustes}R Documentation

Expanded Orthogonal Procrustes Rotation

Description

Expanded Orthogonal Procrustes Rotation

Usage

procoteW(A, C, estm = 0, estW = 0, minW = 0.001, T = NULL, W = NULL,
  m = NULL, maxiter = 200, eps = 1e-06, print = 2)

Arguments

A

The input matrix to be rotated

C

The target matrix

estm

= 1 to estimate m

estW

= 1 to estimate scalar W
= 2 to estimate diagonal W

minW

minimum value of the elements of W

T

Initial value of T or NULL

W

Initial value of W or NULL

m

Initial value of m or NULL

maxiter

max # of iterations

eps

convergence criterion for rmse

print

= 1 to print result

Details

This program finds those A, m, W and orthonormal T which minimize
RSS = tr( ( C - Chat )' ( C - Chat ) )
where Chat = A %*% W %*% T + matrix(1,nv) %*% t(m), W is a diagonal Matrix, T is an orthonormal rotation matrix,
m is the column mean vector.

Note that when estW=0 and estm=0, and the target matrix does not have missing elements,
this is equivalent to the usual orthogonal Procrustes rotation.

Value

A list of:
B=A %*% W %*% T + matrix(1,nv,1)%*%t(m), T, W, , C the updated target matrix, rmse=sqrt(RSS)

Examples

 seed <- 1701; n <- 20; nr <- 2; pmiss <- 0; errstd <- 0.05
 set.seed(seed)
 resg <- gendataWmm( 1, n, nr, genm=1, genW=2, pmiss=pmiss, errstd=errstd)
 A <- resg$A
 C <- resg$C; Tg <- resg$T; mg <- resg$m; Wg <- resg$W
 res <- procoteW( A, C, estm=1, estW=2, print=1 )
 T <- res$T; m <- res$m; W <- res$W
 Print( Tg-T, mg-m, Wg-W, fmt="7.3")



[Package lazy.procrustes version 0.1.3 Index]