MVWNtest {FCVAR}

Multivariate White Noise Tests

Description

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. summary.MVWN_stats prints a summary of these statistics to screen.

Usage

MVWNtest(x, maxlag, printResults)

Arguments

x

A matrix of variables to be included in the system, typically model residuals.

maxlag

The number of lags for serial correlation tests.

printResults

An indicator to print results to screen.

Value

An S3 object of type MVWN_stats containing the test results, including the following parameters:

Q

A 1xp vector of Q statistics for individual series.

pvQ

A 1xp vector of P-values for Q-test on individual series.

LM

A 1xp vector of LM statistics for individual series.

pvLM

A 1xp vector of P-values for LM-test on individual series.

mvQ

A multivariate Q statistic.

pvMVQ

A p-value for multivariate Q-statistic using p^2*maxlag degrees of freedom.

maxlag

The number of lags for serial correlation tests.

p

The number of variables in the system.

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 prints a summary of the MVWN_stats statistics to screen.

Other FCVAR postestimation functions: FCVARboot(), FCVARhypoTest(), GetCharPolyRoots(), 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")]
results <- FCVARestn(x, k = 2, r = 1, opt)
MVWNtest_stats <- MVWNtest(x = results$Residuals, maxlag = 12, printResults = 1)

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)