PMM2fit-class

Class for storing results of linear model estimation using PMM2

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

PMM2fit-class function

<dl>
<dt><code>coefficients</code></dt>
<dd>numeric vector of estimated parameters</dd></dl>
<dt><code>residuals</code></dt>
<dd>numeric vector of final residuals</dd>
<dt><code>m2</code></dt>
<dd>numeric second central moment of initial residuals</dd>
<dt><code>m3</code></dt>
<dd>numeric third central moment of initial residuals</dd>
<dt><code>m4</code></dt>
<dd>numeric fourth central moment of initial residuals</dd>
<dt><code>convergence</code></dt>
<dd>logical or integer code indicating whether algorithm converged</dd>
<dt><code>iterations</code></dt>
<dd>numeric number of iterations performed</dd>
<dt><code>call</code></dt>
<dd>original function call</dd>

Slots

<dl>
<dt>coefficients</dt>
<dd>Estimated coefficients</dd></dl><dt>residuals</dt>
<dd>Final residuals</dd><dt>m2</dt>
<dd>Second central moment</dd><dt>m3</dt>
<dd>Third central moment</dd><dt>m4</dt>
<dd>Fourth central moment</dd><dt>convergence</dt>
<dd>Convergence status</dd><dt>iterations</dt>
<dd>Number of iterations performed</dd><dt>call</dt>
<dd>Original call</dd>

S4 class for storing PMM2 regression model results — PMM2fit-class

<dl>
<dt><code>coefficients</code></dt>
<dd>numeric vector of estimated parameters</dd>


<dt><code>residuals</code></dt>
<dd>numeric vector of final residuals</dd>


<dt><code>m2</code></dt>
<dd>numeric second central moment of initial residuals</dd>


<dt><code>m3</code></dt>
<dd>numeric third central moment of initial residuals</dd>


<dt><code>m4</code></dt>
<dd>numeric fourth central moment of initial residuals</dd>


<dt><code>convergence</code></dt>
<dd>logical or integer code indicating whether algorithm converged</dd>


<dt><code>iterations</code></dt>
<dd>numeric number of iterations performed</dd>


<dt><code>call</code></dt>
<dd>original function call</dd>


</dl>

<dl>
<dt>coefficients</dt>
<dd>Estimated coefficients</dd>

<dt>residuals</dt>
<dd>Final residuals</dd>

<dt>m2</dt>
<dd>Second central moment</dd>

<dt>m3</dt>
<dd>Third central moment</dd>

<dt>m4</dt>
<dd>Fourth central moment</dd>

<dt>convergence</dt>
<dd>Convergence status</dd>

<dt>iterations</dt>
<dd>Number of iterations performed</dd>

<dt>call</dt>
<dd>Original call</dd>


</dl>

PMM2fit-class: S4 class for storing PMM2 regression model results

Description

Arguments

Slots

Slots