makeStreamMeanChangeR

A function, used almost exclusively in testing, to generate a stream
of observations with a certain number of changepoints.

internal

An implementation of the adaptive forgetting factor scheme described in Bodenham and Adams (2016) <doi:10.1007/s11222-016-9684-8> which adaptively estimates the mean and variance of a stream in order to detect multiple changepoints in streaming data. The implementation is in 'C++' and uses 'Rcpp'. Additionally, implementations of the fixed forgetting factor scheme from the same paper, as well as the classic cumulative sum ('CUSUM') and exponentially weighted moving average ('EWMA') methods, are included.

Dean Bodenham

ffstream

Forgetting Factor Methods for Change Detection in Streaming Data

makeStreamMeanChangeR function

<dl><dt>regimeLength</dt>
<dd>The number of observations between changepoints
(before and after). Default is <code>150</code>.</dd>
<dt>seednum</dt>
<dd>The seed for the random number generator. Default is
<code>NULL</code>, in which case no seed will be used.</dd>
<dt>mu0</dt>
<dd>The initial mean of the process.</dd>
<dt>sigma0</dt>
<dd>The variance of each stream.</dd>
<dt>x</dt>
<dd>numChanges The number of changepoints. Default is <code>3</code>.</dd></dl>

Arguments

Create a stream with a certain number of changes — makeStreamMeanChangeR

<dl>

<dt>regimeLength</dt>
<dd>The number of observations between changepoints
(before and after). Default is <code>150</code>.</dd>


<dt>seednum</dt>
<dd>The seed for the random number generator. Default is
<code>NULL</code>, in which case no seed will be used.</dd>


<dt>mu0</dt>
<dd>The initial mean of the process.</dd>


<dt>sigma0</dt>
<dd>The variance of each stream.</dd>


<dt>x</dt>
<dd>numChanges The number of changepoints. Default is <code>3</code>.</dd>

</dl>

makeStreamMeanChangeR: Create a stream with a certain number of changes

Description

Usage

Value

Arguments

Details