EstemPMM: Polynomial Maximization Method for Non-Gaussian Regression

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>.

Version:	0.1.1
Depends:	R (≥ 3.5.0)
Imports:	methods, stats, graphics, utils
Suggests:	dplyr, ggplot2, gridExtra, testthat (≥ 3.0.0), rmarkdown, knitr, MASS
Published:	2025-11-07
DOI:	10.32614/CRAN.package.EstemPMM
Author:	Serhii Zabolotnii [aut, cre]
Maintainer:	Serhii Zabolotnii <zabolotniua at gmail.com>
BugReports:	https://github.com/SZabolotnii/EstemPMM/issues
License:	GPL-3
URL:	https://github.com/SZabolotnii/EstemPMM
NeedsCompilation:	no
Materials:	README, NEWS
CRAN checks:	EstemPMM results

Documentation:

Reference manual:	EstemPMM.html , EstemPMM.pdf
Vignettes:	Bootstrap Inference for PMM2 Models (source, R code) Introduction to PMM2: Polynomial Maximization Method (source, R code) PMM2 for Time Series: AR, MA, ARMA, and ARIMA Models (source, R code)

Downloads:

Package source:	EstemPMM_0.1.1.tar.gz
Windows binaries:	r-devel: EstemPMM_0.1.1.zip, r-release: EstemPMM_0.1.1.zip, r-oldrel: EstemPMM_0.1.1.zip
macOS binaries:	r-release (arm64): EstemPMM_0.1.1.tgz, r-oldrel (arm64): EstemPMM_0.1.1.tgz, r-release (x86_64): EstemPMM_0.1.1.tgz, r-oldrel (x86_64): EstemPMM_0.1.1.tgz

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