Pub Date : 2017-12-10DOI: 10.22034/JIRSS.2017.16.02
M. Mirali, S. Baratpour
{"title":"Some Results on Weighted Cumulative Entropy","authors":"M. Mirali, S. Baratpour","doi":"10.22034/JIRSS.2017.16.02","DOIUrl":"https://doi.org/10.22034/JIRSS.2017.16.02","url":null,"abstract":"","PeriodicalId":42965,"journal":{"name":"JIRSS-Journal of the Iranian Statistical Society","volume":"16 1","pages":"21-32"},"PeriodicalIF":0.4,"publicationDate":"2017-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68033000","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 : 2017-06-25DOI: 10.18869/ACADPUB.JIRSS.16.1.1002
S. M. Zahraie, H. Zakerzadeh
Consider an estimation problem in a one-parameter non-regular distribution when both endpoints of the support depend on a single parameter. In this paper, we give sufficient conditions for a generalized Bayes estimator of a parametric function to be admissible. Some examples are given.
{"title":"Admissibility in a One Parameter Non-regular Family with Squared-log Error Loss Function","authors":"S. M. Zahraie, H. Zakerzadeh","doi":"10.18869/ACADPUB.JIRSS.16.1.1002","DOIUrl":"https://doi.org/10.18869/ACADPUB.JIRSS.16.1.1002","url":null,"abstract":"Consider an estimation problem in a one-parameter non-regular distribution when both endpoints of the support depend on a single parameter. In this paper, we give sufficient conditions for a generalized Bayes estimator of a parametric function to be admissible. Some examples are given.","PeriodicalId":42965,"journal":{"name":"JIRSS-Journal of the Iranian Statistical Society","volume":"16 1","pages":"19-31"},"PeriodicalIF":0.4,"publicationDate":"2017-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42998777","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 : 2017-06-25DOI: 10.18869/ACADPUB.JIRSS.16.1.1005
G. Hamedani
Several characterizations of Marshall-Olkin generalized distributions, introduced by Gui (2013) and by Al-Saiari et al. (2014), are presented. These characterizations are based on: (i) a simple relationship between two truncated moments; (ii) the hazard function.
{"title":"Characterizations of Certain Marshall-Olkin Generalized Distributions","authors":"G. Hamedani","doi":"10.18869/ACADPUB.JIRSS.16.1.1005","DOIUrl":"https://doi.org/10.18869/ACADPUB.JIRSS.16.1.1005","url":null,"abstract":"Several characterizations of Marshall-Olkin generalized distributions, introduced by Gui (2013) and by Al-Saiari et al. (2014), are presented. These characterizations are based on: (i) a simple relationship between two truncated moments; (ii) the hazard function.","PeriodicalId":42965,"journal":{"name":"JIRSS-Journal of the Iranian Statistical Society","volume":"16 1","pages":"69-75"},"PeriodicalIF":0.4,"publicationDate":"2017-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43378292","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 : 2017-06-25DOI: 10.18869/ACADPUB.JIRSS.16.1.1004
M. Abbasnejad
. Recently, a new distribution, named as extended generalized exponential distribution, has been introduced by Kundu and Gupta (2011). In this paper, we con-sider the extended generalized exponential distribution with known shape parameters (cid:11) and (cid:12) . At first, the exact expressions for marginal and product moments of order statistics are derived. Then, these values are used to obtain the necessary coe ffi cients for the best linear unbiased estimators and L-moments estimators of the location and scale parameters. The mean squared errors of these estimators are also given and com-pared.
{"title":"Inferences for Extended Generalized Exponential Distribution based on Order Statistics","authors":"M. Abbasnejad","doi":"10.18869/ACADPUB.JIRSS.16.1.1004","DOIUrl":"https://doi.org/10.18869/ACADPUB.JIRSS.16.1.1004","url":null,"abstract":". Recently, a new distribution, named as extended generalized exponential distribution, has been introduced by Kundu and Gupta (2011). In this paper, we con-sider the extended generalized exponential distribution with known shape parameters (cid:11) and (cid:12) . At first, the exact expressions for marginal and product moments of order statistics are derived. Then, these values are used to obtain the necessary coe ffi cients for the best linear unbiased estimators and L-moments estimators of the location and scale parameters. The mean squared errors of these estimators are also given and com-pared.","PeriodicalId":42965,"journal":{"name":"JIRSS-Journal of the Iranian Statistical Society","volume":"16 1","pages":"53-67"},"PeriodicalIF":0.4,"publicationDate":"2017-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48376786","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 : 2017-06-25DOI: 10.18869/ACADPUB.JIRSS.16.1.1003
مهرداد نادری, علیرضا عربپور, احد جمالیزاده
This paper presents a new finite mixture model using the normal meanvariance mixture of Birnbaum-Saunders distribution. The proposed model is multimodal with wider ranges of skewness and kurtosis. Moreover, it is useful for modeling highly asymmetric data in various theoretical and applied statistical problems. The maximum likelihood estimates of the parameters of the model are computed iteratively by feasible EM algorithm. To illustrate the finite sample properties and performance of the estimators, we conduct a simulation study and illustrate the usefulness of the new model by analyzing a real dataset.
{"title":"مدلسازی آمیخته بر اساس توزیع مخلوط میانگین-واریانس از توزیع نرمال","authors":"مهرداد نادری, علیرضا عربپور, احد جمالیزاده","doi":"10.18869/ACADPUB.JIRSS.16.1.1003","DOIUrl":"https://doi.org/10.18869/ACADPUB.JIRSS.16.1.1003","url":null,"abstract":"This paper presents a new finite mixture model using the normal meanvariance mixture of Birnbaum-Saunders distribution. The proposed model is multimodal with wider ranges of skewness and kurtosis. Moreover, it is useful for modeling highly asymmetric data in various theoretical and applied statistical problems. The maximum likelihood estimates of the parameters of the model are computed iteratively by feasible EM algorithm. To illustrate the finite sample properties and performance of the estimators, we conduct a simulation study and illustrate the usefulness of the new model by analyzing a real dataset.","PeriodicalId":42965,"journal":{"name":"JIRSS-Journal of the Iranian Statistical Society","volume":"6 9 1","pages":"33-51"},"PeriodicalIF":0.4,"publicationDate":"2017-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67675147","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 : 2017-06-25DOI: 10.18869/ACADPUB.JIRSS/20170601
Gholamhossein Gholami
. The problems of sequential change-point have several important appli-cations, including quality control, failure detection in industrial, finance and signal detection. We discuss a Bayesian approach in the context of statistical process control: at an unknown time (cid:28) , the process behavior changes and the distribution of the data changes from p 0 to p 1 . Two cases are considered: (i) p 0 and p 1 are fully known, (ii) p 0 and p 1 belong to the same family of distributions with some unknown parameters (cid:18) 1 , (cid:18) 2 . We present a maximum a posteriori estimate of the change-point which, for the case (i) can be computed in a sequential manner. In addition, we propose the use of the Shiryaev’s loss function. Under this assumption, we define a Bayesian stopping rule. For the Poisson distribution and in the two cases (i) and (ii), we obtain results for the conjugate prior.
{"title":"On the Bayesian Sequential Change-Point Detection","authors":"Gholamhossein Gholami","doi":"10.18869/ACADPUB.JIRSS/20170601","DOIUrl":"https://doi.org/10.18869/ACADPUB.JIRSS/20170601","url":null,"abstract":". The problems of sequential change-point have several important appli-cations, including quality control, failure detection in industrial, finance and signal detection. We discuss a Bayesian approach in the context of statistical process control: at an unknown time (cid:28) , the process behavior changes and the distribution of the data changes from p 0 to p 1 . Two cases are considered: (i) p 0 and p 1 are fully known, (ii) p 0 and p 1 belong to the same family of distributions with some unknown parameters (cid:18) 1 , (cid:18) 2 . We present a maximum a posteriori estimate of the change-point which, for the case (i) can be computed in a sequential manner. In addition, we propose the use of the Shiryaev’s loss function. Under this assumption, we define a Bayesian stopping rule. For the Poisson distribution and in the two cases (i) and (ii), we obtain results for the conjugate prior.","PeriodicalId":42965,"journal":{"name":"JIRSS-Journal of the Iranian Statistical Society","volume":"16 1","pages":"77-94"},"PeriodicalIF":0.4,"publicationDate":"2017-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43934094","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 : 2017-06-10DOI: 10.18869/ACADPUB.JIRSS.16.1.1001
M. Razmkhah, Zahra Saberzade
. The complex system containing n elements, each having three dependent components, is described. The reliability function of such systems is investigated using a trivariate binomial model. In addition, the mean residual life function of a complex system with intact components at time t is derived. The results are simplified for a trivariate Farlie-Gumbel-Morgenstern family with standard exponential marginal distribution functions. The e ff ect of various parameters on the reliability and mean residual life functions are studied via some graphical representations.
{"title":"On the reliability of complex systems with three dependent components per element","authors":"M. Razmkhah, Zahra Saberzade","doi":"10.18869/ACADPUB.JIRSS.16.1.1001","DOIUrl":"https://doi.org/10.18869/ACADPUB.JIRSS.16.1.1001","url":null,"abstract":". The complex system containing n elements, each having three dependent components, is described. The reliability function of such systems is investigated using a trivariate binomial model. In addition, the mean residual life function of a complex system with intact components at time t is derived. The results are simplified for a trivariate Farlie-Gumbel-Morgenstern family with standard exponential marginal distribution functions. The e ff ect of various parameters on the reliability and mean residual life functions are studied via some graphical representations.","PeriodicalId":42965,"journal":{"name":"JIRSS-Journal of the Iranian Statistical Society","volume":"16 1","pages":"1-17"},"PeriodicalIF":0.4,"publicationDate":"2017-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47579392","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 : 2016-08-25DOI: 10.18869/ACADPUB.JIRSS.15.2.87
F. Ghapani, B. Babadi
. In this paper, a new ridge-type estimator is proposed and termed as the new mixed ridge estimator (NMRE) which is obtained by unifying the sample and prior information in linear measurement error model with additional stochastic linear restrictions. The new estimator is a generalization of the mixed estimator (ME) and ridge estimator (RE). The performances of this new estimator and mixed ridge estimator (MRE) with respect to the ME are examined under the criterion of mean squared error matrix. Finally, a numerical example and a Monte Carlo simulation are also presented to analyze.
{"title":"A New Ridge Estimator in Linear Measurement Error Model with Stochastic Linear Restrictions","authors":"F. Ghapani, B. Babadi","doi":"10.18869/ACADPUB.JIRSS.15.2.87","DOIUrl":"https://doi.org/10.18869/ACADPUB.JIRSS.15.2.87","url":null,"abstract":". In this paper, a new ridge-type estimator is proposed and termed as the new mixed ridge estimator (NMRE) which is obtained by unifying the sample and prior information in linear measurement error model with additional stochastic linear restrictions. The new estimator is a generalization of the mixed estimator (ME) and ridge estimator (RE). The performances of this new estimator and mixed ridge estimator (MRE) with respect to the ME are examined under the criterion of mean squared error matrix. Finally, a numerical example and a Monte Carlo simulation are also presented to analyze.","PeriodicalId":42965,"journal":{"name":"JIRSS-Journal of the Iranian Statistical Society","volume":"15 1","pages":"87-103"},"PeriodicalIF":0.4,"publicationDate":"2016-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67675059","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 : 2016-08-25DOI: 10.18869/ACADPUB.JIRSS.15.2.73
A. Kiapour, M. N. Qomi
. Shrinkage preliminary test estimation in exponential distribution under a precautionary loss function is considered. The minimum risk-unbiased estimator is derived and some shrinkage preliminary test estimators are proposed. We apply our results on censored data and records. The relative e ffi ciencies of proposed estimators with respect to the minimum risk-unbiased estimator based on record data under the considered loss function are computed for evaluating the performance of these estimators.
{"title":"Shrinkage Preliminary Test Estimation under a Precautionary Loss Function with Applications on Records and Censored Ddata","authors":"A. Kiapour, M. N. Qomi","doi":"10.18869/ACADPUB.JIRSS.15.2.73","DOIUrl":"https://doi.org/10.18869/ACADPUB.JIRSS.15.2.73","url":null,"abstract":". Shrinkage preliminary test estimation in exponential distribution under a precautionary loss function is considered. The minimum risk-unbiased estimator is derived and some shrinkage preliminary test estimators are proposed. We apply our results on censored data and records. The relative e ffi ciencies of proposed estimators with respect to the minimum risk-unbiased estimator based on record data under the considered loss function are computed for evaluating the performance of these estimators.","PeriodicalId":42965,"journal":{"name":"JIRSS-Journal of the Iranian Statistical Society","volume":"15 1","pages":"73-85"},"PeriodicalIF":0.4,"publicationDate":"2016-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67675442","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 : 2016-08-25DOI: 10.18869/ACADPUB.JIRSS.15.2.105
G. Hesamian
This paper considers the classical (normal) Bayesian method for testing fuzzy hypotheses. For this purpose, using a notion of prior distribution with interval-valued or fuzzy-valued parameters, a concept of posterior probability of a fuzzy hypothesis is proposed and its main properties are also verified. The feasibility and effectiveness of the proposed methods are also clarified by some numerical examples.
{"title":"Bayesian Fuzzy Hypothesis Testing with Imprecise Prior Distribution","authors":"G. Hesamian","doi":"10.18869/ACADPUB.JIRSS.15.2.105","DOIUrl":"https://doi.org/10.18869/ACADPUB.JIRSS.15.2.105","url":null,"abstract":"This paper considers the classical (normal) Bayesian method for testing fuzzy hypotheses. For this purpose, using a notion of prior distribution with interval-valued or fuzzy-valued parameters, a concept of posterior probability of a fuzzy hypothesis is proposed and its main properties are also verified. The feasibility and effectiveness of the proposed methods are also clarified by some numerical examples.","PeriodicalId":42965,"journal":{"name":"JIRSS-Journal of the Iranian Statistical Society","volume":"15 1","pages":"105-119"},"PeriodicalIF":0.4,"publicationDate":"2016-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67675155","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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