Improved Likelihood Inference Procedures for the Logistic Distribution
<p dir="ltr">We consider third-order likelihood inferences for the parameters, quantiles and reliability function of the logistic distribution. This theory involves the conditioning and marginalization of the likelihood function. The logistic distribution is a symmetric distribution...
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2022
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| _version_ | 1864513548799967232 |
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| author | Ayman Baklizi (14158944) |
| author_facet | Ayman Baklizi (14158944) |
| author_role | author |
| dc.creator.none.fl_str_mv | Ayman Baklizi (14158944) |
| dc.date.none.fl_str_mv | 2022-08-01T00:00:00Z |
| dc.identifier.none.fl_str_mv | 10.3390/sym14091767 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Improved_Likelihood_Inference_Procedures_for_the_Logistic_Distribution/29021621 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Mathematical sciences Statistics likelihood ratio statistic third order inference logistic distribution ancillary directions conditioning Barndorff-Nielsen’s formula |
| dc.title.none.fl_str_mv | Improved Likelihood Inference Procedures for the Logistic Distribution |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">We consider third-order likelihood inferences for the parameters, quantiles and reliability function of the logistic distribution. This theory involves the conditioning and marginalization of the likelihood function. The logistic distribution is a symmetric distribution which is closely related to normal distributions, and which has several applications because of its mathematical tractability and the availability of a closed-form cumulative distribution function. The performance of the third-order techniques is investigated and compared with the first-order techniques using simulations. The results show that the third-order techniques are far more accurate than the usual first-order inference procedures. This results in more accurate inferences about the functions of the parameters of the distribution, which leads to more precise conclusions about the phenomenon modeled by the logistic distribution.</p><h2>Other Information</h2><p dir="ltr">Published in: Symmetry<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3390/sym14091767" target="_blank">https://dx.doi.org/10.3390/sym14091767</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_c4585fcc057da22c283d2dcbea529668 |
| identifier_str_mv | 10.3390/sym14091767 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/29021621 |
| publishDate | 2022 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Improved Likelihood Inference Procedures for the Logistic DistributionAyman Baklizi (14158944)Mathematical sciencesStatisticslikelihood ratio statisticthird order inferencelogistic distributionancillary directionsconditioningBarndorff-Nielsen’s formula<p dir="ltr">We consider third-order likelihood inferences for the parameters, quantiles and reliability function of the logistic distribution. This theory involves the conditioning and marginalization of the likelihood function. The logistic distribution is a symmetric distribution which is closely related to normal distributions, and which has several applications because of its mathematical tractability and the availability of a closed-form cumulative distribution function. The performance of the third-order techniques is investigated and compared with the first-order techniques using simulations. The results show that the third-order techniques are far more accurate than the usual first-order inference procedures. This results in more accurate inferences about the functions of the parameters of the distribution, which leads to more precise conclusions about the phenomenon modeled by the logistic distribution.</p><h2>Other Information</h2><p dir="ltr">Published in: Symmetry<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3390/sym14091767" target="_blank">https://dx.doi.org/10.3390/sym14091767</a></p>2022-08-01T00:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.3390/sym14091767https://figshare.com/articles/journal_contribution/Improved_Likelihood_Inference_Procedures_for_the_Logistic_Distribution/29021621CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/290216212022-08-01T00:00:00Z |
| spellingShingle | Improved Likelihood Inference Procedures for the Logistic Distribution Ayman Baklizi (14158944) Mathematical sciences Statistics likelihood ratio statistic third order inference logistic distribution ancillary directions conditioning Barndorff-Nielsen’s formula |
| status_str | publishedVersion |
| title | Improved Likelihood Inference Procedures for the Logistic Distribution |
| title_full | Improved Likelihood Inference Procedures for the Logistic Distribution |
| title_fullStr | Improved Likelihood Inference Procedures for the Logistic Distribution |
| title_full_unstemmed | Improved Likelihood Inference Procedures for the Logistic Distribution |
| title_short | Improved Likelihood Inference Procedures for the Logistic Distribution |
| title_sort | Improved Likelihood Inference Procedures for the Logistic Distribution |
| topic | Mathematical sciences Statistics likelihood ratio statistic third order inference logistic distribution ancillary directions conditioning Barndorff-Nielsen’s formula |