This function computes an estimation of the risk for the tapered covariance matrix estimator of a process via a bootstrap method, for a specified treshold and a specified kernel.
Rboot(epsilon, treshold, block_size, block_n, model_max, kernel_fonc)numeric vector. An univariate process.
integer. Number of estimated autocovariance terms that we consider for the estimation of the covariance matrix.
integer. The size of the bootstrap blocks. block_size must be greater than model_max.
integer. Blocks number used for the bootstrap.
integer. The maximal dimension, that is the maximal number of terms available to estimate the covariance matrix.
function. The kernel to use. The user can define his own kernel and put it in the argument.
This function returns a list with:
for one treshold, the value of the estimated risk.
the standard-error due to the bootstrap.
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.