cov_AR {slm} | R Documentation |
Fit an autoregressive model to the process and compute the theoretical autocovariances of the fitted AR process.
By default, the order is chosen by using the AIC criterion (model_selec = -1
).
cov_AR(epsilon, model_selec = -1, plot = FALSE)
epsilon |
numeric vector. An univariate process. |
model_selec |
integer or |
plot |
logical. By default, |
The function returns the vector of the theoretical autocovariances of the AR process fitted on the process epsilon
.
model_selec |
the order selected. |
cov_st |
the vector of theoretical autocovariances of the fitted AR process. |
P.J. Brockwell and R.A. Davis (1991). Time Series: Theory and Methods. Springer Science & Business Media.
E. Caron, J. Dedecker and B. Michel (2019). Linear regression with stationary errors: the R package slm. arXiv preprint arXiv:1906.06583. https://arxiv.org/abs/1906.06583.
x = arima.sim(list(ar=c(0.4,0.2)),1000)
cov_AR(x, model_selec = 2, plot = TRUE)