model_score

Calculates the modeling score of a GMWM

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 

model_score function

<dl><dt>A</dt>
<dd>A <code>mat</code> that contains the first derivatives of the processes</dd>
<dt>omega</dt>
<dd>A <code>mat</code> that contains the omega used when calculating the GMWM</dd>
<dt>v_hat</dt>
<dd>A <code>mat</code> that contains the covariance matrix</dd>
<dt>At_j</dt>
<dd>A <code>mat</code> that contains the second derivative of each process</dd>
<dt>diff</dt>
<dd>A <code>vec</code> that is the difference of the WV empirical and WV theoretical</dd></dl>

Arguments

Model Score — model_score

<dl>

<dt>A</dt>
<dd>A <code>mat</code> that contains the first derivatives of the processes</dd>


<dt>omega</dt>
<dd>A <code>mat</code> that contains the omega used when calculating the GMWM</dd>


<dt>v_hat</dt>
<dd>A <code>mat</code> that contains the covariance matrix</dd>


<dt>At_j</dt>
<dd>A <code>mat</code> that contains the second derivative of each process</dd>


<dt>diff</dt>
<dd>A <code>vec</code> that is the difference of the WV empirical and WV theoretical</dd>

</dl>

Model Score

model_score: Model Score

Description

Usage

Value

Arguments

Details