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# CITATION file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "EstemPMM" in publications use:'
type: software
license: GPL-3.0-only
title: 'EstemPMM: Polynomial Maximization Method for Non-Gaussian Regression'
version: 0.4.0
doi: 10.32614/CRAN.package.EstemPMM
abstract: 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. The 'PMM3' variant
  (S=3) targets symmetric platykurtic error distributions, reducing variance when
  excess kurtosis is negative. Includes automatic method selection ('pmm_dispatch'),
  linear regression, 'AR'/'MA'/'ARMA'/'ARIMA' models, and bootstrap inference. Methodology
  described in Zabolotnii, Warsza, and Tkachenko (2018) <https://doi.org/10.1007/978-3-319-77179-3_75>,
  Zabolotnii, Tkachenko, and Warsza (2022) <https://doi.org/10.1007/978-3-031-03502-9_37>,
  and Zabolotnii, Tkachenko, and Warsza (2023) <https://doi.org/10.1007/978-3-031-25844-2_21>,
  and Zabolotnii (2025) <https://doi.org/10.48550/arXiv.2511.07059>.
authors:
- family-names: Zabolotnii
  given-names: Serhii
  email: zabolotniua@gmail.com
  orcid: https://orcid.org/0000-0003-0242-2234
repository: https://szabolotnii.r-universe.dev
repository-code: https://github.com/SZabolotnii/EstemPMM
commit: 718925a6ddcdf4599f7a0c60fc24cc021f3db5c9
url: https://github.com/SZabolotnii/EstemPMM
date-released: '2026-05-28'
contact:
- family-names: Zabolotnii
  given-names: Serhii
  email: zabolotniua@gmail.com
  orcid: https://orcid.org/0000-0003-0242-2234