gen_mean

Generate a determinist vector returned by the matrix by vector product of matrix \(X\) and vector \(\beta\).

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 

gen_mean function

<dl><dt>X</dt>
<dd>A <code>Matrix</code> with dimension n*p.</dd>
<dt>beta</dt>
<dd>A <code>vector</code> with dimension p*1</dd></dl>

Arguments

Generate a determinist vector returned by the matrix by vector product of matrix \(X\) and vector \(\beta\). — gen_mean

<dl>

<dt>X</dt>
<dd>A <code>Matrix</code> with dimension n*p.</dd>


<dt>beta</dt>
<dd>A <code>vector</code> with dimension p*1</dd>

</dl>

Generate a determinist vector returned by the matrix by vector product of matrix \(X\) and vector \(\beta\).

gen_mean: Generate a determinist vector returned by the matrix by vector product of matrix \(X\) and vector \(\beta\).

Description

Usage

Value

Arguments