WARp_acvfs {WRI}R Documentation

Function for calculating sample Wasserstein autocovariance functions

Description

This function uses a time series of quantile functions to calculate the sample Wasserstein autocovariance functions from order 0 to p with a specified training window

Usage

WARp_acvfs(end.day, training.size, quantile, quantile.grid, p)

Arguments

end.day

A positive integer, the last index of the training window.

training.size

A positive integer, the size of the training widnows.

quantile

A matrix containing all the available quantile functions. Columns represent time indices and rows represent evaluation grid.

quantile.grid

A numeric vector, the grid over which quantile functions are evaluated.

p

A positive integer, the maximum order of the sample Wasserstein autocovariance functions.

Value

A list with


[Package WRI version 0.2.0 Index]