Sample_ACV

Calculating sample autocovariance of a specified lag for a centered time series

internal

Implementation of the methodologies described in 1) Alexander Petersen, Xi Liu and Afshin A. Divani (2021) <doi:10.1214/20-aos1971>, including global F tests, partial F tests, intrinsic Wasserstein-infinity bands and Wasserstein density bands, and 2) Chao Zhang, Piotr Kokoszka and Alexander Petersen (2022) <doi:10.1111/jtsa.12590>, including estimation, prediction, and inference of the Wasserstein autoregressive models.

Xi Liu

Wasserstein Regression and Inference

Chao Zhang

Matthew Coleman

Alexander Petersen

Sample_ACV function

<dl><dt>ts</dt>
<dd>A numeric vector consisting of sequentially collected data</dd>
<dt>lag</dt>
<dd>A positive integer indicates the lag of the autocovariance function</dd></dl>

Arguments

Function for calculating sample autocovariance — Sample_ACV

<dl>

<dt>ts</dt>
<dd>A numeric vector consisting of sequentially collected data</dd>


<dt>lag</dt>
<dd>A positive integer indicates the lag of the autocovariance function</dd>

</dl>

Sample_ACV: Function for calculating sample autocovariance

Description

Usage

Value

Arguments