lik_ar: Likelihood of an autoregressive time series model with i.i.d....

In beyondWhittle: Bayesian Spectral Inference for Time Series

Likelihood of an autoregressive time series model with i.i.d. normal innovations

Description

Likelihood of an autoregressive time series model with i.i.d. normal innovations

Usage

lik_ar(x, ar, mean = 0, sd = 1, log = F, full = T)

Arguments

x	numeric vector of data
ar	vector of ar parameters
mean	the innovation mean
sd	the innovation standard deviation
log	logical; if TRUE, probabilities p are given as log(p)
full	logical; if TRUE, the full likelihood for all observations is computed; if FALSE, the partial likelihood for the last n-p observations

Value

numeric value for the likelihood or log-likelihood

beyondWhittle documentation built on April 3, 2025, 7:49 p.m.