FCVARhypoTest: Test of Restrictions on FCVAR Model

In FCVAR: Estimation and Inference for the Fractionally Cointegrated VAR

Test of Restrictions on FCVAR Model

Description

FCVARhypoTest performs a likelihood ratio test of the null hypothesis: "model is modelR" against the alternative hypothesis: "model is modelUNR".

Usage

FCVARhypoTest(modelUNR, modelR)

Arguments

modelUNR	A list of estimation results created for the unrestricted model.
modelR	A list of estimation results created for the restricted model.

Value

A list LRtest containing the test results, including the following parameters:

loglikUNR

The log-likelihood for the unrestricted model.

loglikR

The log-likelihood for the restricted model.

df

The degrees of freedom for the test.

LRstat

The likelihood ratio test statistic.

p_LRtest

The p-value for the likelihood ratio test.

See Also

The test is calculated using the results of two calls to FCVARestn, under the restricted and unrestricted models. Use FCVARoptions to set default estimation options for each model, then set restrictions as needed before FCVARestn.

Other FCVAR postestimation functions: FCVARboot(), GetCharPolyRoots(), MVWNtest(), plot.FCVAR_roots(), summary.FCVAR_roots(), summary.MVWN_stats()

Examples

opt <- FCVARoptions()
opt$gridSearch   <- 0 # Disable grid search in optimization.
opt$dbMin        <- c(0.01, 0.01) # Set lower bound for d,b.
opt$dbMax        <- c(2.00, 2.00) # Set upper bound for d,b.
opt$constrained  <- 0 # Impose restriction dbMax >= d >= b >= dbMin ? 1 <- yes, 0 <- no.
x <- votingJNP2014[, c("lib", "ir_can", "un_can")]
m1 <- FCVARestn(x, k = 2, r = 1, opt)
opt1 <- opt
opt1$R_psi <- matrix(c(1, 0), nrow = 1, ncol = 2)
opt1$r_psi <- 1
m1r1 <- FCVARestn(x, k = 2, r = 1, opt1)
Hdb <- FCVARhypoTest(modelUNR = m1, modelR = m1r1)



opt1 <- opt
opt1$R_Beta <- matrix(c(1, 0, 0), nrow = 1, ncol = 3)
m1r2 <- FCVARestn(x, k = 2, r = 1, opt1)
Hbeta1 <- FCVARhypoTest(m1, m1r2)



opt1 <- opt
opt1$R_Alpha <- matrix(c(0, 1, 0), nrow = 1, ncol = 3)
m1r4 <- FCVARestn(x, k = 2, r = 1, opt1)
Halpha2 <- FCVARhypoTest(m1, m1r4)

FCVAR documentation built on May 5, 2022, 9:06 a.m.