predict,PMM2fit-method

Prediction method for PMM2fit 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

predict,PMM2fit-method function

<dl><dt>object</dt>
<dd>PMM2fit object</dd>
<dt>newdata</dt>
<dd>New data frame for prediction</dd>
<dt>debug</dt>
<dd>Logical value, whether to output debug information</dd>
<dt>...</dt>
<dd>additional arguments (not used)</dd></dl>

Arguments

Prediction method for PMM2fit objects — predict,PMM2fit-method

<dl>

<dt>object</dt>
<dd>PMM2fit object</dd>


<dt>newdata</dt>
<dd>New data frame for prediction</dd>


<dt>debug</dt>
<dd>Logical value, whether to output debug information</dd>


<dt>...</dt>
<dd>additional arguments (not used)</dd>

</dl>

predict,PMM2fit-method: Prediction method for PMM2fit objects

Description

Usage

Value

Arguments