summary.MVWN_stats: Summarize Statistics for Multivariate White Noise Tests

In FCVAR: Estimation and Inference for the Fractionally Cointegrated VAR

Summarize Statistics for Multivariate White Noise Tests

Description

summary.MVWN_stats is an S3 method for objects of class MVWN_stats that prints a summary of the statistics from MVWNtest to screen. MVWNtest performs multivariate tests for white noise. It performs both the Ljung-Box Q-test and the LM-test on individual series for a sequence of lag lengths.

Usage

## S3 method for class 'MVWN_stats'
summary(object, ...)

Arguments

object	An S3 object of type MVWN_stats containing the results from multivariate tests for white noise. It is the output of MVWNtest.
...	additional arguments affecting the summary produced.

Note

The LM test is consistent for heteroskedastic series, the Q-test is not.

See Also

FCVARoptions to set default estimation options. FCVARestn produces the residuals intended for this test. LagSelect uses this test as part of the lag order selection process. summary.MVWN_stats is an S3 method for class MVWN_stats that prints a summary of the output of MVWNtest to screen.

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

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")]
results <- FCVARestn(x, k = 2, r = 1, opt)
MVWNtest_stats <- MVWNtest(x = results$Residuals, maxlag = 12, printResults = 1)
summary(object = MVWNtest_stats)



set.seed(27)
WN <- stats::rnorm(100)
RW <- cumsum(stats::rnorm(100))
MVWN_x <- as.matrix(data.frame(WN = WN, RW = RW))
MVWNtest_stats <- MVWNtest(x = MVWN_x, maxlag = 10, printResults = 1)
summary(object = MVWNtest_stats)

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