Locally Stationary Whittle Log-likelihood sigma

Source: R/ls_whittle_loglik_sd.R

This function calculates log-likelihood with known \(\theta\), through LS.whittle.loglik function.

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).