evalEtaNu

Evaluation of the variances Eta2 and Nu2

Detect abrupt changes in time series with local fluctuations as a random walk process and autocorrelated noise as an AR(1) process. See Romano, G., Rigaill, G., Runge, V., Fearnhead, P. (2021) <doi:10.1080/01621459.2021.1909598>.

Gaetano Romano

DeCAFS

Detecting Changes in Autocorrelated and Fluctuating Signals

Guillem Rigaill

Vincent Runge

Paul Fearnhead

evalEtaNu function

<dl><dt>v</dt>
<dd>the estimated variances of the diff k operator</dd>
<dt>phi</dt>
<dd>the autocorrelative AR(1) parameter</dd>
<dt>sdEta</dt>
<dd>if sdEta = FALSE there is no random walk</dd></dl>

Arguments

RW and AR(1) variance estimations with fixed AR(1) parameter — evalEtaNu

<dl>

<dt>v</dt>
<dd>the estimated variances of the diff k operator</dd>


<dt>phi</dt>
<dd>the autocorrelative AR(1) parameter</dd>


<dt>sdEta</dt>
<dd>if sdEta = FALSE there is no random walk</dd>

</dl>

evalEtaNu: RW and AR(1) variance estimations with fixed AR(1) parameter

Description

Usage

Value

Arguments