FCVARhypoTest | R Documentation |
FCVARhypoTest
performs a likelihood ratio test of the null
hypothesis: "model is modelR
" against the alternative hypothesis:
"model is modelUNR
".
FCVARhypoTest(modelUNR, modelR)
modelUNR |
A list of estimation results created for the unrestricted model. |
modelR |
A list of estimation results created for the restricted model. |
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.
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()
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)
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