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#' @title Locally Stationary Whittle Log-likelihood sigma
#' @description This function calculates log-likelihood with known \eqn{\theta},
#' through \code{LS.whittle.loglik} function.
#' @details
#' This function computes \code{\link{LS.whittle.loglik}} with \code{x} as
#' \code{x = c(theta.par, x)}.
#' @param x (type: numeric) parameter vector.
#' @param series (type: numeric) univariate time series.
#' @param order (type: numeric) vector corresponding to \code{ARMA} model
#' entered.
#' @param ar.order (type: numeric) AR polimonial order.
#' @param ma.order (type: numeric) MA polimonial order.
#' @param sd.order (type: numeric) polinomial order noise scale factor.
#' @param d.order (type: numeric) \code{d} polinomial order, where \code{d} is
#' the \code{ARFIMA} parameter.
#' @param include.d (type: numeric) logical argument for \code{ARFIMA} models.
#' If \code{include.d=FALSE} then the model is an ARMA process.
#' @param N (type: numeric) value corresponding to the length of the window to
#' compute periodogram. If \code{N=NULL} then the function will use
#' \eqn{N = \textrm{trunc}(n^{0.8})}, see Dahlhaus (1998) where \eqn{n} is the
#' length of the \code{y} vector.
#' @param S (type: numeric) value corresponding to the lag with which will go
#' taking the blocks or windows.
#' @param include.taper (type: logical) logical argument that by default is
#' \code{TRUE}. See \code{\link{periodogram}}.
#' @param theta.par (type: numeric) vector with the known parameters of the
#' model.
#' @export
LS.whittle.loglik.sd <- function(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()) {
x <- c(theta.par, x)
LS.whittle.loglik(x = x, series = series, order = order, ar.order = ar.order, ma.order = ma.order, sd.order = sd.order, d.order = d.order, include.d = include.d, N = N, S = S, include.taper = include.taper)
}
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