TB_AR_test: Computes Tiao-Box Test for Autocorrelation.

In multDM: Multivariate Version of the Diebold-Mariano Test

Computes Tiao-Box Test for Autocorrelation.

Description

This function computes Tiao-Box test for autocorrelation, i.e, coefficient of p-th lag in VAR(p) model. Its null hypothesis is that p-th lag is not essential. The alternative hypothesis is that it is essential.

Usage

TB_AR_test(d,p)

Arguments

d	matrix of time-series, assumed to be the stationary VARMA type, columns correspond to time index, and rows to different time-series
p	numeric indicating a lag length beyond which we are willing to assume that the autocorrelation is essentially zero

Value

class htest object, list of

statistic	test statistic
parameter	q, a lag length
alternative	alternative hypothesis of the test
p.value	p-value
method	name of the test
data.name	name of the tested time-series

References

Tiao, G.C., Box, G.E.P. 1981. Modeling multiple times series with applications. Journal of the American Statistical Association 76, 802–816.

Examples

data(MDMforecasts)
ts <- MDMforecasts$ts
forecasts <- MDMforecasts$forecasts
l <- loss(realized=ts,evaluated=forecasts,loss.type="SE")
d <- d_t(l)
TB_AR_test(d=d,p=10)

multDM documentation built on June 9, 2022, 5:06 p.m.