Pub Date : 2021-09-01DOI: 10.1007/s44199-021-00001-5
Haruka Murayama, Shota Saito, Yuji Iikubo, Yuta Nakahara, T. Matsushima
{"title":"Cluster’s Number Free Bayes Prediction of General Framework on Mixture of Regression Models","authors":"Haruka Murayama, Shota Saito, Yuji Iikubo, Yuta Nakahara, T. Matsushima","doi":"10.1007/s44199-021-00001-5","DOIUrl":"https://doi.org/10.1007/s44199-021-00001-5","url":null,"abstract":"","PeriodicalId":45080,"journal":{"name":"Journal of Statistical Theory and Applications","volume":"46 1","pages":"425 - 449"},"PeriodicalIF":1.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81515361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-09DOI: 10.2991/jsta.d.210616.002
F. Younis, M. Aslam, M. Bhatti
Recently, El-Sherpieny et al (2020) suggested Type -II hybrid censoring method for parametric estimation of Lomax distribution (LD) without due regards being given to the choice of priors and posterior risk associated with the model. This paper fills this gap and derived the new LDmodel with minimum posterior risk for the selection of priors. It derives a closed form expression for Bayes estimates and posterior risks using Square error loss function (SELF), Weighted loss function (WLF), Quadratic loss function (QLF) and Degroot loss function (DLF). Prior predictive approach is used to elicit the hyper parameters of mixture model. Analysis of Bayes estimates and posterior risks is presented in terms of sample size (n), mixing proportion ( p ) and censoring rate ( 0 t ), with the help of simulation study. Usefulness of the model is demonstrated on applying it to simulated and real-life data which show promising results in terms of better estimation and risk reduction.
{"title":"Preference of Prior for Two-Component Mixture of Lomax Distribution","authors":"F. Younis, M. Aslam, M. Bhatti","doi":"10.2991/jsta.d.210616.002","DOIUrl":"https://doi.org/10.2991/jsta.d.210616.002","url":null,"abstract":"Recently,\u0000El-Sherpieny et al (2020) suggested Type -II hybrid censoring method for\u0000parametric estimation of Lomax distribution (LD) without due regards being\u0000given to the choice of priors and posterior risk associated with the model.\u0000This paper fills this gap and derived the new LDmodel with minimum posterior\u0000risk for the selection of priors. It derives a closed form expression for Bayes\u0000estimates and posterior risks using Square error loss function (SELF), Weighted\u0000loss function (WLF), Quadratic loss function (QLF) and Degroot loss function (DLF).\u0000Prior predictive approach is used to elicit the hyper parameters of mixture\u0000model. Analysis of Bayes estimates and posterior risks is presented in terms of\u0000sample size (n), mixing proportion ( p ) and censoring rate ( 0 t ), with\u0000the help of simulation study. Usefulness of the model is demonstrated on applying\u0000it to simulated and real-life data which show promising results in terms of\u0000better estimation and risk reduction.","PeriodicalId":45080,"journal":{"name":"Journal of Statistical Theory and Applications","volume":"20 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2021-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89794604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.2991/jsta.d.210607.002
Sofi Mudasir, S. Ahmad
{"title":"Parameter Estimation of the Weighted Generalized Inverse Weibull Distribution","authors":"Sofi Mudasir, S. Ahmad","doi":"10.2991/jsta.d.210607.002","DOIUrl":"https://doi.org/10.2991/jsta.d.210607.002","url":null,"abstract":"","PeriodicalId":45080,"journal":{"name":"Journal of Statistical Theory and Applications","volume":"6 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80898849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.2991/jsta.d.210607.001
Sarra Chouia, Halim zeghdoudi
{"title":"The XLindley Distribution: Properties and Application","authors":"Sarra Chouia, Halim zeghdoudi","doi":"10.2991/jsta.d.210607.001","DOIUrl":"https://doi.org/10.2991/jsta.d.210607.001","url":null,"abstract":"","PeriodicalId":45080,"journal":{"name":"Journal of Statistical Theory and Applications","volume":"28 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88277912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.2991/jsta.d.210610.001
Manoj Chacko, P. Asha
{"title":"Estimation of Entropy for Weibull Distribution Based on Record Values","authors":"Manoj Chacko, P. Asha","doi":"10.2991/jsta.d.210610.001","DOIUrl":"https://doi.org/10.2991/jsta.d.210610.001","url":null,"abstract":"","PeriodicalId":45080,"journal":{"name":"Journal of Statistical Theory and Applications","volume":"64 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80019784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-01DOI: 10.2991/JSTA.D.210609.001
M. Alizadeh, M. Afshari, H. Karamikabir, H. Yousof
In this paper, a new class of distributions called the odd log-logistic Burr-X family with two extra positive parameters is introduced and studied. The new generator extends the odd log-logistic and Burr X distributions among several other well-known distributions.We provide somemathematical properties of the new family including asymptotics, moments, moment-generating function and incomplete moments. Different methods have been used to estimate its parameters such as maximum likelihood, least squares, weighted least squares, Cramer–von-Mises, Anderson–Darling and right-tailed Anderson–Darling methods. We evaluate the performance of the maximum likelihood estimators in terms of biases and mean squared errors by means of a simulation study. Finally, the usefulness of the family is illustrated by means of three real data sets. The new models provide consistently better fits than other competitive models for these data sets. The new family is suitable for fitting different real data sets, the odd log-logistic Burr-XNormalmodel is used formodeling bimodal and skewed data sets and can be sued as an alternative to the gamma-normal, beta-normal, McDonald-normal, Marshall-Olkin-normal, Kumaraswamy-normal, Zografos-Balakrishnan and Log-normal distributions.
{"title":"The Odd Log-Logistic Burr-X Family of Distributions: Properties and Applications","authors":"M. Alizadeh, M. Afshari, H. Karamikabir, H. Yousof","doi":"10.2991/JSTA.D.210609.001","DOIUrl":"https://doi.org/10.2991/JSTA.D.210609.001","url":null,"abstract":"In this paper, a new class of distributions called the odd log-logistic Burr-X family with two extra positive parameters is introduced and studied. The new generator extends the odd log-logistic and Burr X distributions among several other well-known distributions.We provide somemathematical properties of the new family including asymptotics, moments, moment-generating function and incomplete moments. Different methods have been used to estimate its parameters such as maximum likelihood, least squares, weighted least squares, Cramer–von-Mises, Anderson–Darling and right-tailed Anderson–Darling methods. We evaluate the performance of the maximum likelihood estimators in terms of biases and mean squared errors by means of a simulation study. Finally, the usefulness of the family is illustrated by means of three real data sets. The new models provide consistently better fits than other competitive models for these data sets. The new family is suitable for fitting different real data sets, the odd log-logistic Burr-XNormalmodel is used formodeling bimodal and skewed data sets and can be sued as an alternative to the gamma-normal, beta-normal, McDonald-normal, Marshall-Olkin-normal, Kumaraswamy-normal, Zografos-Balakrishnan and Log-normal distributions.","PeriodicalId":45080,"journal":{"name":"Journal of Statistical Theory and Applications","volume":"16 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87794167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-01DOI: 10.2991/jsta.d.210616.001
Muhammad Tahir, M. Ahsanullah, Sidra Mohsin, M. Abid
{"title":"On Finite 3-Component Mixture of Rayleigh Distributions: A Classical Look","authors":"Muhammad Tahir, M. Ahsanullah, Sidra Mohsin, M. Abid","doi":"10.2991/jsta.d.210616.001","DOIUrl":"https://doi.org/10.2991/jsta.d.210616.001","url":null,"abstract":"","PeriodicalId":45080,"journal":{"name":"Journal of Statistical Theory and Applications","volume":"135 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88637185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-01DOI: 10.2991/JSTA.D.210602.001
J. Saran, Kanika Verma, Narinder Pushkarna
{"title":"Relationships for Moments of Generalized Order Statistics from Hjorth Distribution and Related Inference","authors":"J. Saran, Kanika Verma, Narinder Pushkarna","doi":"10.2991/JSTA.D.210602.001","DOIUrl":"https://doi.org/10.2991/JSTA.D.210602.001","url":null,"abstract":"","PeriodicalId":45080,"journal":{"name":"Journal of Statistical Theory and Applications","volume":"18 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86941284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-05-01DOI: 10.2991/JSTA.D.210510.001
M. R. Mahmoud, H. Muhammed, Ahmed R. El-Saeed, Ashraf D. Abdellatif
{"title":"Estimation of Parameters of the GIE Distribution Under Progressive Type-I Censoring","authors":"M. R. Mahmoud, H. Muhammed, Ahmed R. El-Saeed, Ashraf D. Abdellatif","doi":"10.2991/JSTA.D.210510.001","DOIUrl":"https://doi.org/10.2991/JSTA.D.210510.001","url":null,"abstract":"","PeriodicalId":45080,"journal":{"name":"Journal of Statistical Theory and Applications","volume":"38 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77535053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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