LS.whittle.loglik.sd: Locally Stationary Whittle Log-likelihood sigma In LSTS: Locally Stationary Time Series

Description

This function calculates log-likelihood with known θ, through `LS.whittle.loglik` function.

Usage

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14``` ```LS.whittle.loglik.sd( 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, theta.par = numeric() ) ```

Arguments

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

Details

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

LSTS documentation built on July 29, 2021, 5:07 p.m.