plot_pmm2_bootstrap

Plot bootstrap distributions for PMM2 fit

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_pmm2_bootstrap function

<dl><dt>object</dt>
<dd>Result from pmm2_inference</dd>
<dt>coefficients</dt>
<dd>Which coefficients to plot, defaults to all</dd></dl>

Arguments

Plot bootstrap distributions for PMM2 fit — plot_pmm2_bootstrap

<dl>

<dt>object</dt>
<dd>Result from pmm2_inference</dd>


<dt>coefficients</dt>
<dd>Which coefficients to plot, defaults to all</dd>

</dl>

plot_pmm2_bootstrap: Plot bootstrap distributions for PMM2 fit

Description

Usage

Value

Arguments