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The Logit Exponentiated Power Exponential Regression with Applications

The Logit Exponentiated Power Exponential Regression with Applications We introduce a new distribution, called the logit exponentiated power exponential, defined on the unit interval. Explicit expansions are derived for its moments. Also, we propose a regression based on this distribution with two systematic components, which can provide better fits than the beta and simplex regressions. Its parameters are estimated by maximum likelihood. Some simulations investigate the accuracy of the estimates. The usefulness of the new models is proved by means of three real data sets. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Annals of Data Science Springer Journals

The Logit Exponentiated Power Exponential Regression with Applications

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References (27)

Publisher
Springer Journals
Copyright
Copyright © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021
ISSN
2198-5804
eISSN
2198-5812
DOI
10.1007/s40745-021-00347-8
Publisher site
See Article on Publisher Site

Abstract

We introduce a new distribution, called the logit exponentiated power exponential, defined on the unit interval. Explicit expansions are derived for its moments. Also, we propose a regression based on this distribution with two systematic components, which can provide better fits than the beta and simplex regressions. Its parameters are estimated by maximum likelihood. Some simulations investigate the accuracy of the estimates. The usefulness of the new models is proved by means of three real data sets.

Journal

Annals of Data ScienceSpringer Journals

Published: Jun 1, 2023

Keywords: Beta regression; Exponentiated power exponential distribution; Likelihood inference; Residual analysis

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