gendataWmm {lazy.procrustes}R Documentation

Generation of Procscal Data

Description

Generation of Procscal Data

Usage

gendataWmm(ns, nv, nr, genm = 0, genW = 0, genT = 1, genW2 = 0,
  genmu = 0, mu0 = 0, genD1 = 0, genD2 = 0, eqm = 0, eqW = 0,
  eqT = 0, eqW2 = 0, diagW2 = 1, eqD1 = 0, eqD2 = 0, genV = 0,
  diagV = 1, pcA = 0, errstd = 0, pmiss = 0, minWD = 0.2)

Arguments

ns

# of matrices to be generated.

nv

# of rows of the matrices to be rotated.

nr

# of columns of the matrices to be rotated.

genm

= 1 to generate m vectors, the column mean

genW

= 1 to generate scalar W matrices, the left weight
= 2 to generate diagonal W matrices, the left weight

genT

= 0 to skip the generation of T matrices, the rotation

genW2

= 1 to generate W2 matrices, the right weigt

genmu

= 1 to generate mu matrix

mu0

The common value of mu

genD1

= 1 to generate D1 matrices,

genD2

= 1 to generate D2 matrices,

eqm

= 1 to generate common m

eqW

= 1 to generate common W

eqT

= 1 to generate common T

eqW2

= 1 to generate common W2

diagW2

= 0 to make W2 non-diagonal

eqD1

= 1 to generate common WD1

eqD2

= 1 to generate common D2

genV

= 1 to generate V matrix

diagV

= 0 to make V non-diagonal

pcA

= 1 to make the column variances of A equal
= 2 to column orthogonalize A

errstd

std of errors to be added to final C matrix

pmiss

= proportion of missing elements of C matrix

minWD

= minimum value of W and D matrices

Details

This program generates A, mk, Tk, Wk, W2k, D1k, D2k matrices
so that the k-th target matrix Ck is created as
Ck = inv(D1k) ( A Wk Tk W2k + 1 mk' ) inv(D2k) + Ek, k=1,2,...,ns,
where Disp(Ek) = errstd^2*solve(V).

When genmu=1, we set genm=0; genD1=0; genD2=0; genW2=0; genV=0 and
muk = mu0 + A uk
will be generated via uk where muk is nv x 1 and uk is nr x 1.

For examples, see procotWKS or procscal.

Value

A list of all the matrices and the parameter values.


[Package lazy.procrustes version 0.1.3 Index]