simple_diag_plot

This function will plot four diagnostic plots to assess how well the model fits 
the data. These plots are: (1) residuals plot, (2) histogram of 
(standardized) residuals, (3) normal Q-Q plot of residuals and (4) residuals vs fitted values plot.

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 

simple_diag_plot function

<dl><dt>Xt</dt>
<dd>The original time series data.</dd>
<dt>model</dt>
<dd>The <code>arima</code> model fit to the data.</dd>
<dt>std</dt>
<dd>A <code>boolean</code> indicating whether we use standardized residuals for the 
(1) residuals plot and the (2) histogram of (standardized) residuals.</dd></dl>

Arguments

Author

Basic Diagnostic Plot of Residuals — simple_diag_plot

<dl>

<dt>Xt</dt>
<dd>The original time series data.</dd>


<dt>model</dt>
<dd>The <code>arima</code> model fit to the data.</dd>


<dt>std</dt>
<dd>A <code>boolean</code> indicating whether we use standardized residuals for the 
(1) residuals plot and the (2) histogram of (standardized) residuals.</dd>

</dl>

Basic Diagnostic Plot of Residuals

simple_diag_plot: Basic Diagnostic Plot of Residuals

Description

Usage

Arguments

Author