MVWNtest | R Documentation |
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.
MVWNtest(x, maxlag, printResults)
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. |
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.
The LM test is consistent for heteroskedastic series; the Q-test is not.
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()
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)
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