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EstemPMM  

Polynomial Maximization Method for Non-Gaussian Regression
View on CRAN: Click here


Download and install EstemPMM package within the R console
Install from CRAN:
install.packages("EstemPMM")

Install from Github:
library("remotes")
install_github("cran/EstemPMM")

Install by package version:
library("remotes")
install_version("EstemPMM", "0.1.1")



Attach the package and use:
library("EstemPMM")
Maintained by
Serhii Zabolotnii
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-11-07
Latest Update: 2025-11-07
Description:
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>.
How to cite:
Serhii Zabolotnii (2025). EstemPMM: Polynomial Maximization Method for Non-Gaussian Regression. R package version 0.1.1, https://cran.r-project.org/web/packages/EstemPMM. Accessed 12 Sep. 2026.
Previous versions and publish date:
0.1.1 (2025-11-07 14:50), 0.3.1 (2026-04-07 07:20), 0.3.2 (2026-05-15 22:10), (2026-07-09 08:03)
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Complete documentation for EstemPMM
Functions, R codes and Examples using the EstemPMM R package
Full EstemPMM package functions and examples
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