gscmcovfr: 'gscmcovfr' determines the covariance matrix of a GSC model...

Description Usage Arguments Value Examples

View source: R/CovGSCmodel_fr.r

Description

gscmcovfr determines the covariance matrix of a GSC model belonging to scenario fr. The covariance matrices of the errors are supposed to be diagonal.

Usage

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gscmcovfr(B, indicatorx, indicatory, lambday, wx, Sxixi, R2 = NULL)

Arguments

B

(q,q) lower triangular matrix describing the interrelations of the latent variables: b_ij = 1 regression coefficient of eta_j in the regression relation in which eta_i is the depend variable b_ij = 0 if eta_i does not depend on eta_j in a direct way (b_ii = 0 !)

indicatorx

vector describing with which exogenous composite the X-variables are connected

indicatory

vector describing with which endogenous composite the Y-variables are connected

lambday

vector of loadings of indicators for endogenous composites

wx

vector of weights for building exogenous composites

Sxixi

covariance matrix of exogenous composites

R2

vector of coefficients of determination for regressions belonging to the structural model

Value

out list with components

S covariance matrix of manifest variables
B (q,q) lower triangular matrix with possibly modified coefficients of the structural model
Scomp covariance matrix of composites
wx vector of weights for building exogenous composites
See diagonal matrix of variances of errors of Y variable loadings or NA

Examples

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Sxixi <- matrix(c(1.0,  0.01,  0.01, 1),2,2)   
B <- matrix(c( 0,0,0, 0,0,0, 0.7,0.4,0),3,3,byrow=TRUE) 
indicatorx <- c(1,1,1,2,2,2)
indicatory <- c(1,1,1)  
lambday <- c(0.89,0.90,0.80)    
wx <- c(0.46, 0.31, 0.32, 0.34, 0.40, 0.37) 
out <- gscmcovfr(B,indicatorx,indicatory,lambday,wx,Sxixi,R2=NULL)      

cbsem documentation built on May 2, 2019, 5:56 a.m.

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