Test of covariance structure for PFC models

Description

Information criterion and likelihood ratio test for the structure of the covariance matrix of PFC models.

Usage

structure.test(object1, object2)

Arguments

Details

Consider two PFC models M_1 and M_2, with the same parameters, except for the conditional covariance that is Δ_1 for M_1 and Δ_2 for M_2 such that model M_1 is nested in model M_2. We implemented the likelihood ratio test for the hypotheses: H_0: Δ=Δ_1 versus H_a: Δ=Δ_2. The test is implemented for the isotropic, anisotropic, and the unstructured PFC models. One may test isotropic against either anisotropic or unstructured, or test anisotropic against unstructured. The degrees of freedom are given by the difference in the number of parameters in the covariances. Information criterion AIC and BIC are also provided.

Author(s)

Kofi Placid Adragni <kofi@umbc.edu>

Examples

data(bigmac)
fit1 <- pfc(X=bigmac[,-1], y=bigmac[,1], fy=bf(y=bigmac[,1], case="poly", 
        degree=3), numdir=3, structure="iso")
fit2 <- pfc(X=bigmac[,-1], y=bigmac[,1], fy=bf(y=bigmac[,1], case="poly", 
        degree=3), numdir=3, structure="aniso")
fit3 <- pfc(X=bigmac[,-1], y=bigmac[,1], fy=bf(y=bigmac[,1], case="poly", 
        degree=3), numdir=3, structure="unstr")
structure.test(fit1, fit3)
structure.test(fit2, fit3)

Results