parcovmatlist: Compute asymptotic covariance matrix for PAR model

In GeoBosh/pcts: Periodically Correlated and Periodically Integrated Time Series

Compute asymptotic covariance matrix for PAR model

Description

Compute asymptotic covariance matrix for PAR model

Usage

parcovmatlist(parmodel, n, cor = FALSE, result = "list")

Arguments

parmodel	PAR model, object of class parModel
n	length of the series or a vector with one element for each season.
cor	If TRUE return correlation matrix.
result	if "list", the default, return a list, if "Matrix" return a Matrix object, otherwise return an ordinary matrix, see Details.

Details

Uses eq. (3.3) in the reference.

If result = "list", parcovmatlist returns a list whose s-th element is the covariance matrix of the PAR parameters for the s-th season. Otherwise, if result = "Matrix" it returns a block-diagonal matrix created by .bdiag() from package "Matrix". If result = "matrix" it returns an ordinary matrix (with the current implementation this is returned for any value other than "list" or "Matriix").

Value

a list, matrix or block-diagonal matrix, as described in Details

Author(s)

Georgi N. Boshnakov

References

\insertRef

McLeod1994diagnosticpcts

See Also

pcacfMat, pc.acf.parModel

Examples

x <- arima.sim(list(ar=0.9), n=1000)
proba1 <- fitPM(c(3,2,2,2), x)

parcovmatlist(proba1, 100)
parcovmatlist(proba1, 100, cor = TRUE)
sqrt(diag(parcovmatlist(proba1, 100, cor = TRUE)[[1]]))

meanvarcheck(proba1, 100)

GeoBosh/pcts documentation built on Dec. 8, 2023, 9:57 p.m.