e_drift

This function computes the expected value of a drift process.

internal

A system contains easy-to-use tools as a support for time series analysis courses. In particular, it incorporates a technique called Generalized Method of Wavelet Moments (GMWM) as well as its robust implementation for fast and robust parameter estimation of time series models which is described, for example, in Guerrier et al. (2013) <doi: 10.1080/01621459.2013.799920>. More details can also be found in the paper linked to via the URL below.

St<c3><a9>phane Guerrier

simts

Time Series Analysis Tools

Stéphane Guerrier

James Balamuta

Roberto Molinari

Justin Lee

Lionel Voirol

Yuming Zhang

Wenchao Yang

Nathanael Claussen

Yunxiang Zhang

Christian Gunning

Romain Francois

Ross Ihaka

R Core Team 

e_drift function

<dl><dt>omega</dt>
<dd>A <code>double</code> corresponding to variance of drift.</dd>
<dt>n_ts</dt>
<dd>An <code>int</code> indicating the length of the time series.</dd></dl>

Arguments

Expected value DR — e_drift

<dl>

<dt>omega</dt>
<dd>A <code>double</code> corresponding to variance of drift.</dd>


<dt>n_ts</dt>
<dd>An <code>int</code> indicating the length of the time series.</dd>

</dl>

Expected value DR

e_drift: Expected value DR

Description

Usage

Value

Arguments