mixAR (version 0.22.8)

fit_mixVAR-methods: Fit mixture vector autoregressive models

Description

Estimate a MixVAR model for a multivariate time series. This is a generic function. The methods defined in package MixAR are described here.

Usage

fit_mixVAR(x, model, fix, ...)

Value

a MixVAR model.

Arguments

x

a multivariate time series (currently a numeric matrix).

model

model, object inheriting from MixVAR class.

fix

if TRUE, fix the shift parameters.

...

additional arguments for the methods (not currently used).

Methods

signature(x = "ANY", model = "MixVAR")

signature(x = "ANY", model = "ANY")

Details

model specifies the model to fit. If model inherits from "MixVAR", it is used as a template. Estimation is done via EM-Algorithm, using the function mixVARfit.

Currently the default method for fit_mixAR just throws error, since there seems no suitable default task to do.

See Also

mixVARfit

Examples

AR <- list()
AR[[1]] <- array(c(0.5, -0.3, -0.6, 0, 0, 0.5, 0.4, 0.5, -0.3), dim = c(3, 3, 1))
AR[[2]] <- array(c(-0.5, 0.3, 0, 1, 0, -0.5, -0.4, -0.2, 0.5), dim = c(3, 3, 1))

prob <- c(0.75, 0.25)
shift <- cbind(c(0, 0, 0), c(0, 0, 0))

Sigma1 <- cbind(c(1, 0.5, -0.4), c(0.5, 2, 0.8), c(-0.4, 0.8, 4))
Sigma2 <- cbind(c(1, 0.2, 0), c(0.2,  2, -0.15), c(0, -0.15, 4))
Sigma <- array(c(Sigma1, Sigma2), dim = c(3, 3, 2))

m <- new("MixVARGaussian", prob = prob, vcov = Sigma, arcoef = AR, shift = shift)

set.seed(1234)
y <- mixVAR_sim(m, n = 100, init = matrix(0, ncol = 3), nskip = 50, flag = FALSE)

fit_mixVAR(y, m, tol = 1e-3)
mixVARfit(y, m, tol = 1e-3)