plot,TS2fit,missing-method

Build diagnostic plots for TS2fit objects

Implements the Polynomial Maximization Method ('PMM') for parameter estimation
in linear and time series models when error distributions deviate from normality.
The 'PMM2' variant achieves lower variance parameter estimates compared to ordinary
least squares ('OLS') when errors exhibit significant skewness. Includes methods
for linear regression, 'AR'/'MA'/'ARMA'/'ARIMA' models, and bootstrap inference.
Methodology described in Zabolotnii, Warsza, and Tkachenko (2018) <doi:10.1007/978-3-319-77179-3_75>,
Zabolotnii, Tkachenko, and Warsza (2022) <doi:10.1007/978-3-031-03502-9_37>, and
Zabolotnii, Tkachenko, and Warsza (2023) <doi:10.1007/978-3-031-25844-2_21>.

Serhii Zabolotnii

EstemPMM

Polynomial Maximization Method for Non-Gaussian Regression

plot,TS2fit,missing-method function

<dl><dt>x</dt>
<dd>TS2fit object</dd>
<dt>y</dt>
<dd>Not used (for S4 method compatibility)</dd>
<dt>which</dt>
<dd>Integer vector indicating which plots to produce</dd>
<dt>...</dt>
<dd>additional arguments passed to plot functions</dd></dl>

Arguments

Build diagnostic plots for TS2fit objects — plot,TS2fit,missing-method

<dl>

<dt>x</dt>
<dd>TS2fit object</dd>


<dt>y</dt>
<dd>Not used (for S4 method compatibility)</dd>


<dt>which</dt>
<dd>Integer vector indicating which plots to produce</dd>


<dt>...</dt>
<dd>additional arguments passed to plot functions</dd>

</dl>

plot,TS2fit,missing-method: Build diagnostic plots for TS2fit objects

Description

Usage

Value

Arguments