initAFFMean

This function makes it simple to initalise an AFF object.

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

initAFFMean function

<dl><dt>eta</dt>
<dd>The value of the step size in the gradient descent. 
Default is eta=0.01.</dd></dl>

Arguments

Initialisation of AFF mean — initAFFMean

<dl>

<dt>eta</dt>
<dd>The value of the step size in the gradient descent. 
Default is eta=0.01.</dd>

</dl>

initAFFMean: Initialisation of AFF mean

Description

Usage

Value

Arguments

Examples