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Article: Squared normal model and its generalization for the analysis of skewed positive data

TitleSquared normal model and its generalization for the analysis of skewed positive data
Authors
KeywordsMM algorithm
newton–raphson algorithm
skewed positive data
squared normal distribution
squared skew-normal distribution
Issue Date18-Dec-2023
PublisherTaylor and Francis Group
Citation
Communications in Statistics - Simulation and Computation, 2023, p. 1-21 How to Cite?
Abstract

To model skewed positive data with high kurtosis, this paper proposes, a new squared normal (SQN) distribution, which is constructed by squaring the normal random variable with non-zero mean and non-unit variance. The SQN distribution can be regarded as an extension of the chi-squared distribution, which cannot be applied to directly modeling real-life data. Some distributional properties, parameter estimation methods and hypothesis testings are investigated for the SQN distribution itself and the corresponding regression model. Furthermore, a generalization to a squared skew-normal (SSN) distribution is proposed by incorporating an additional skew parameter, improving the flexibility of the model. Finally, simulation experiments are conducted and a real data set is analyzed to demonstrate the proposed methodologies.


Persistent Identifierhttp://hdl.handle.net/10722/346181
ISSN
2023 Impact Factor: 0.8
2023 SCImago Journal Rankings: 0.440

 

DC FieldValueLanguage
dc.contributor.authorLiu, Xuanyu-
dc.contributor.authorZhang, Chi-
dc.contributor.authorYuen, Kam Chuen-
dc.contributor.authorTian, Guo-Liang-
dc.date.accessioned2024-09-12T00:30:42Z-
dc.date.available2024-09-12T00:30:42Z-
dc.date.issued2023-12-18-
dc.identifier.citationCommunications in Statistics - Simulation and Computation, 2023, p. 1-21-
dc.identifier.issn0361-0918-
dc.identifier.urihttp://hdl.handle.net/10722/346181-
dc.description.abstract<p>To model skewed positive data with high kurtosis, this paper proposes, a new squared normal (SQN) distribution, which is constructed by squaring the normal random variable with non-zero mean and non-unit variance. The SQN distribution can be regarded as an extension of the chi-squared distribution, which cannot be applied to directly modeling real-life data. Some distributional properties, parameter estimation methods and hypothesis testings are investigated for the SQN distribution itself and the corresponding regression model. Furthermore, a generalization to a squared skew-normal (SSN) distribution is proposed by incorporating an additional skew parameter, improving the flexibility of the model. Finally, simulation experiments are conducted and a real data set is analyzed to demonstrate the proposed methodologies.</p>-
dc.languageeng-
dc.publisherTaylor and Francis Group-
dc.relation.ispartofCommunications in Statistics - Simulation and Computation-
dc.subjectMM algorithm-
dc.subjectnewton–raphson algorithm-
dc.subjectskewed positive data-
dc.subjectsquared normal distribution-
dc.subjectsquared skew-normal distribution-
dc.titleSquared normal model and its generalization for the analysis of skewed positive data-
dc.typeArticle-
dc.identifier.doi10.1080/03610918.2023.2293649-
dc.identifier.scopuseid_2-s2.0-85180203514-
dc.identifier.spage1-
dc.identifier.epage21-
dc.identifier.eissn1532-4141-
dc.identifier.issnl0361-0918-

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