tscov.tsmarch: Covariance Extractor

In tsmarch: Multivariate ARCH Models

Covariance Extractor

Description

Extracts the conditional covariance matrices.

Usage

## S3 method for class 'cgarch.estimate'
tscov(object, distribution = TRUE, ...)

## S3 method for class 'cgarch.simulate'
tscov(object, distribution = TRUE, ...)

## S3 method for class 'cgarch.predict'
tscov(object, distribution = TRUE, ...)

## S3 method for class 'dcc.estimate'
tscov(object, distribution = TRUE, ...)

## S3 method for class 'dcc.simulate'
tscov(object, distribution = TRUE, ...)

## S3 method for class 'dcc.predict'
tscov(object, distribution = TRUE, ...)

## S3 method for class 'gogarch.estimate'
tscov(object, distribution = TRUE, ...)

## S3 method for class 'gogarch.predict'
tscov(object, distribution = TRUE, ...)

## S3 method for class 'gogarch.simulate'
tscov(object, distribution = TRUE, ...)

Arguments

object	an object class from one of the models in the package.
distribution	whether to return the full simulated covariance distribution for the predicted and simulated objects, else the average covariance across each horizon.
...	none

Details

Estimation Object

An array of covariance matrices with time as the third dimension. The returned object has attributes ‘index’ representing the datetime and ‘series’ representing the series names.

Simulation and Prediction Objects

A 4-d array of dimensions (n_series x n_series x horizon x n_draws). If distribution is FALSE, then the average covariance across all draws, an array of dimensions (n_series x n_series x horizon).

Value

the covariance (see details).

Author(s)

Alexios Galanos

tsmarch documentation built on April 3, 2025, 7:40 p.m.