get.gg

Computes quantities required for data-driven selection of the average block size for stationary bootstrap

internal

Binary segmentation methods for detecting and estimating multiple change-points in the mean or second-order structure of high-dimensional time series as described in Cho and Fryzlewicz (2014) <doi:10.1111/rssb.12079> and Cho (2016) <doi:10.1214/16-EJS1155>.

Haeran Cho

hdbinseg

Change-Point Analysis of High-Dimensional Time Series via Binary
Segmentation

Piotr Fryzlewicz

get.gg function

<dl><dt>z</dt>
<dd>univariate time series</dd>
<dt>M</dt>
<dd>bandwidth, by default, <code>M = NULL</code> to be automatically selected as in Politis and White (2004)</dd>
<dt>C</dt>
<dd><code>C = 2</code> is the default value chosen for automatic bandwidth selection in Politis and White (2004)</dd>
<dt>max.K</dt>
<dd><code>max.K = 5</code> is the default value chosen for automatic bandwidth selection in Politis and White (2004)</dd></dl>

Arguments

Data-driven selection of the average block size — get.gg

<dl>

<dt>z</dt>
<dd>univariate time series</dd>


<dt>M</dt>
<dd>bandwidth, by default, <code>M = NULL</code> to be automatically selected as in Politis and White (2004)</dd>


<dt>C</dt>
<dd><code>C = 2</code> is the default value chosen for automatic bandwidth selection in Politis and White (2004)</dd>


<dt>max.K</dt>
<dd><code>max.K = 5</code> is the default value chosen for automatic bandwidth selection in Politis and White (2004)</dd>

</dl>

get.gg: Data-driven selection of the average block size

Description

Usage

Value

Arguments

References