vma.sim: Compute The Vector of Moving Average Model (VMA)

In portes: Portmanteau Tests for Time Series Models

Compute The Vector of Moving Average Model (VMA)

Description

This utility function is useful to use in the function varima.sim and may used to compute the coefficients of moving-average or vector moving-average.

Usage

vma.sim(psi, a)

Arguments

psi	the impulse coefficients.
a	innovations

Value

Vector of length n (in the univariate case), or n matrices (in the multivariate case), where n = length(a)-length(\Psi) and n\times k is the dimension of the series.

Author(s)

Esam Mahdi and A.I. McLeod.

References

Hannan, E.J. (1970). "Multiple Time Series". New York: Wiley.

Hipel, K.W. and McLeod, A.I. (2005). "Time Series Modelling of Water Resources and Environmental Systems".

See Also

convolve, varima.sim, arima.sim, ImpulseVMA, InvertQ

Examples

k <- 2
n <- 300
trunc.lag <-  50   
ar <-  array(c(0.5,0.4,0.1,0.5),dim=c(k,k,1))
ma <-  array(c(0,0.25,0,0),dim=c(k,k,1))
sigma <- matrix(c(1,0.71,0.71,2),k,k)
p <- ifelse(is.null(ar),0,dim(ar)[3])
q <- ifelse(is.null(ma),0,dim(ma)[3])
r <- max(p, q)
d <- trunc.lag + r
psi <- ImpulseVMA(ar = ar, ma = ma, trunc.lag = trunc.lag)
a <- t(crossprod(chol(sigma),matrix(rnorm(k*d),ncol=d)))
vma.sim(psi = psi, a = a)

portes documentation built on July 9, 2023, 5:07 p.m.