FactorCopulaModel (version 0.1.1)

corDis: Discrepancy of model-based and observed correlation matrices based on Gaussian log-likelihood

Description

Discrepancy of model-based and observed correlation matrices

Usage

corDis(Rmodel,Rdata,n=0,npar=0)

Value

vector with discrepancy Dfit, and also nllk2 (wice negative log-likelihood), BIC, AIC if n and npar are inputted

Arguments

Rmodel

model-based correlation matrix

Rdata

empirical correlation matrix (could be observed or polychoric)

n

sample size (if positive integer)

npar

#parameters in the correlation structure

Examples

Rmodel = matrix(c(1,.3,.4,.4,.3,1,.5,.6,.4,.5,1,.7,.4,.6,.7,1),4,4)
print(Rmodel); print(chol(Rmodel))
Rdata = matrix(c(1,.32,.38,.41,.32,1,.53,.61,.38,.53,1,.67,.41,.61,.67,1),4,4)
print(corDis(Rmodel,Rdata))
print(corDis(Rmodel,Rdata,n=400,npar=3))