cov_select {slm}

Covariances Selection

Description

Allows the user to select the lags of the autocovariance terms of the process to be kept.

Usage

cov_select(epsilon, model_selec, plot = FALSE)

Arguments

epsilon

numeric vector. An univariate process.

model_selec

a vector with the positive lags of the selected autocovariance terms. The variance (lag = 0) is automatically selected.

plot

logical. By default, plot = FALSE. If plot = TRUE the ACF of the process is plotted.

Details

In the framework of slm, this is a manual method for estimating the covariance matrix of the error process by only selecting some autocovariance terms from the residual autocovariances.

Value

This function returns the estimated autocovariance terms.

model_selec

the vector with the positive lag of the selected autocovariance terms.

cov_st

the vector of the selected autocovariances.

References

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.

Examples

x = arima.sim(list(ar=c(0.2,0.1,0.25)),1000)
cov_select(x, c(1,3,5))