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- Publisher Website: 10.1080/03610918.2023.2293649
- Scopus: eid_2-s2.0-85180203514
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Article: Squared normal model and its generalization for the analysis of skewed positive data
Title | Squared normal model and its generalization for the analysis of skewed positive data |
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Authors | |
Keywords | MM algorithm newton–raphson algorithm skewed positive data squared normal distribution squared skew-normal distribution |
Issue Date | 18-Dec-2023 |
Publisher | Taylor 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 Identifier | http://hdl.handle.net/10722/346181 |
ISSN | 2023 Impact Factor: 0.8 2023 SCImago Journal Rankings: 0.440 |
DC Field | Value | Language |
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dc.contributor.author | Liu, Xuanyu | - |
dc.contributor.author | Zhang, Chi | - |
dc.contributor.author | Yuen, Kam Chuen | - |
dc.contributor.author | Tian, Guo-Liang | - |
dc.date.accessioned | 2024-09-12T00:30:42Z | - |
dc.date.available | 2024-09-12T00:30:42Z | - |
dc.date.issued | 2023-12-18 | - |
dc.identifier.citation | Communications in Statistics - Simulation and Computation, 2023, p. 1-21 | - |
dc.identifier.issn | 0361-0918 | - |
dc.identifier.uri | http://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.language | eng | - |
dc.publisher | Taylor and Francis Group | - |
dc.relation.ispartof | Communications in Statistics - Simulation and Computation | - |
dc.subject | MM algorithm | - |
dc.subject | newton–raphson algorithm | - |
dc.subject | skewed positive data | - |
dc.subject | squared normal distribution | - |
dc.subject | squared skew-normal distribution | - |
dc.title | Squared normal model and its generalization for the analysis of skewed positive data | - |
dc.type | Article | - |
dc.identifier.doi | 10.1080/03610918.2023.2293649 | - |
dc.identifier.scopus | eid_2-s2.0-85180203514 | - |
dc.identifier.spage | 1 | - |
dc.identifier.epage | 21 | - |
dc.identifier.eissn | 1532-4141 | - |
dc.identifier.issnl | 0361-0918 | - |