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Last data update: 2014.03.03

R: Locally Stationary Whittle Log-likelihood theta

LS.whittle.loglik.theta

R Documentation

Locally Stationary Whittle Log-likelihood theta

Description

Calculate the log-likelihood with σ known, through LS.whittle.loglik function.

Usage

LS.whittle.loglik.theta(x, series, order = c(p = 0, q = 0), ar.order = NULL,
                        ma.order = NULL, sd.order = NULL, d.order = NULL,
                        include.d = FALSE, N = NULL, S = NULL, 
                        include.taper = TRUE, sd.par = 1)

Arguments

`x`	parameter vector.
`series`	univariate time series.
`order`	vector with the specification of the ARMA model: the two integer components (p, q) are the AR order and the MA order.
`ar.order, ma.order`	AR and MA polimonial order respectively.
`sd.order`	polinomial order noise scale factor.
`d.order`	`d` polinomial order, where `d` is the `ARFIMA` parameter.
`include.d`	logical argument for `ARFIMA` models. If `include.d=FALSE` then the model is an ARMA process.
`N`	value corresponding to the length of the window to compute periodogram. If `N=NULL` then the function will use N = \textmd{trunc}(n^{0.8}), see Dahlhaus (1998) where n is the length of the `y` vector.
`S`	value corresponding to the lag with which will go taking the blocks or windows.
`include.taper`	logical argument that by default is `TRUE`. See `periodogram`.
`sd.par`	value corresponding to known variance.

Details

This function computes LS.whittle.loglik with x as x = c(x, sd.par).

Author(s)