cv_trunc: Truncate data, with truncation parameter chosen by...

View source: R/truncate.R

cv_truncR Documentation

Truncate data, with truncation parameter chosen by cross-validation.

Description

Truncate data, with truncation parameter chosen by cross-validation.

Usage

cv_trunc(data, n_tau = 60, lag = 0, cv_lag = 0, standardise = TRUE)

Arguments

data

Input time series each column representing a time series variable.

n_tau

An integer that determines the number of taus to use in grid used for cross-validation

lag

This is an integer argument that is used when the cv_trunc function is used for (auto)covariance estimation, of particular lag. The lag determines which (auto)covariance matrix is used in tuning.

cv_lag

An integer argument, that is used when the cv_trunc function is used with data modeled as a factor-adjusted VAR. The integer determines up to what lag auto-covariance matrix is used in the cv-measure. In implementation, this will be set as default to be the VAR order. When cv_lag = 0, only the (auto)covariance matrix, of lag determined by the lag argument, is used.

standardise

boolean; whether to scale up the truncation parameter for each series by the MAD of the corresponding series.


Dom-Owens-UoB/fnets documentation built on Nov. 22, 2024, 7:09 a.m.