Likelihood-based inference for the power regression model

In this paper we investigate an extension of the power-normal model, called the alpha-power model and specialize it to linear and nonlinear regression models, with and without correlated errors. Maximum likelihood estimation is considered with explicit derivation of the observed and expected Fisher...

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Bibliographic Details
Authors: Martínez-Flórez, Guillermo; Bolfarine, Heleno; Gómez, Héctor W.
Format: Article
Publication date:2015
Country:España
Institution:Universitat Politècnica de Catalunya (UPC)
Repository:UPCommons. Portal del coneixement obert de la UPC
Language:English
OAI Identifier:oai:upcommons.upc.edu:2117/88527
Online Access:https://hdl.handle.net/2117/88527
Access Level:Open access
Keyword:Correlation
maximum likelihood
power-normal distribution
regression.
Classificació AMS::60 Probability theory and stochastic processes::60E Distribution theory
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
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author Martínez-Flórez, Guillermo
author2 Bolfarine, Heleno
Gómez, Héctor W.
author2_role author
author
author_browse Bolfarine, Heleno
Gómez, Héctor W.
Martínez-Flórez, Guillermo
author_facet Martínez-Flórez, Guillermo
Bolfarine, Heleno
Gómez, Héctor W.
author_role author
collection UPCommons. Portal del coneixement obert de la UPC
description In this paper we investigate an extension of the power-normal model, called the alpha-power model and specialize it to linear and nonlinear regression models, with and without correlated errors. Maximum likelihood estimation is considered with explicit derivation of the observed and expected Fisher information matrices. Applications are considered for the Australian athletes data set and also to a data set studied in Xie et al. (2009). The main conclusion is that the proposed model can be a viable alternative in situations were the normal distribution is not the most adequate model.
eu_rights_str_mv openAccess
format article
id ES_4039d008b28dcc3a514b70e0bc585ce7
institution Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
language eng
network_acronym_str ES
network_name_str España
oai_identifier_str oai:upcommons.upc.edu:2117/88527
publishDate 2015
publishDateSort 2015
publisher Institut d'Estadística de Catalunya
publisherStr Institut d'Estadística de Catalunya
reponame_str UPCommons. Portal del coneixement obert de la UPC
spelling Likelihood-based inference for the power regression model Martínez-Flórez, Guillermo Bolfarine, Heleno Gómez, Héctor W. Correlation maximum likelihood power-normal distribution regression. Classificació AMS::60 Probability theory and stochastic processes::60E Distribution theory Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica In this paper we investigate an extension of the power-normal model, called the alpha-power model and specialize it to linear and nonlinear regression models, with and without correlated errors. Maximum likelihood estimation is considered with explicit derivation of the observed and expected Fisher information matrices. Applications are considered for the Australian athletes data set and also to a data set studied in Xie et al. (2009). The main conclusion is that the proposed model can be a viable alternative in situations were the normal distribution is not the most adequate model. Peer Reviewed Institut d'Estadística de Catalunya https://hdl.handle.net/2117/88527
spellingShingle Likelihood-based inference for the power regression model
Martínez-Flórez, Guillermo
Correlation
maximum likelihood
power-normal distribution
regression.
Classificació AMS::60 Probability theory and stochastic processes::60E Distribution theory
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
title Likelihood-based inference for the power regression model
title_full Likelihood-based inference for the power regression model
title_fullStr Likelihood-based inference for the power regression model
title_full_unstemmed Likelihood-based inference for the power regression model
title_short Likelihood-based inference for the power regression model
title_sort Likelihood-based inference for the power regression model
topic Correlation
maximum likelihood
power-normal distribution
regression.
Classificació AMS::60 Probability theory and stochastic processes::60E Distribution theory
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
topic_facet Correlation
maximum likelihood
power-normal distribution
regression.
Classificació AMS::60 Probability theory and stochastic processes::60E Distribution theory
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
url https://hdl.handle.net/2117/88527