Pub Date : 2013-03-24DOI: 10.18869/ACADPUB.JSRI.10.1.85
Z. Javanshiri, A. H. Rad, H. Hamedani
In this paper, we study properties of exp-uniform distribution and its applications. We provide closed forms for the density function and moments of order statistics and we also discuss estimation of the parameters via the maximum likelihood method. We will present certain characteriza- tions of exp-uniform distribution. The applications of this distribution are illustrated by fitting it to three real data sets and comparing the results with other lifetime distributions. We hope that this distribution will attract wider applications in lifetime models.
{"title":"Exp-Uniform Distribution: Properties and Characterizations","authors":"Z. Javanshiri, A. H. Rad, H. Hamedani","doi":"10.18869/ACADPUB.JSRI.10.1.85","DOIUrl":"https://doi.org/10.18869/ACADPUB.JSRI.10.1.85","url":null,"abstract":"In this paper, we study properties of exp-uniform distribution and its applications. We provide closed forms for the density function and moments of order statistics and we also discuss estimation of the parameters via the maximum likelihood method. We will present certain characteriza- tions of exp-uniform distribution. The applications of this distribution are illustrated by fitting it to three real data sets and comparing the results with other lifetime distributions. We hope that this distribution will attract wider applications in lifetime models.","PeriodicalId":422124,"journal":{"name":"Journal of Statistical Research of Iran","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128908369","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 : 2013-03-15DOI: 10.18869/ACADPUB.JSRI.9.2.179
G. Barmalzan, T. P. Najafabad
Consider the problem of estimating true density, h(·) based upon a random sample X1, . . . , Xn. In general, h(·) is approximated using an appropriate (in some sense, see below) model fθ(x). This article using Vuong’s (1989) test along with a collection of k(> 2) non-nested models constructs a set of appropriate models, say model confidence set, for unknown model h(·). Application of such confidence set has been confirmed through a simulation study.
{"title":"Model Confidence Set Based on Kullback-Leibler Divergence Distance","authors":"G. Barmalzan, T. P. Najafabad","doi":"10.18869/ACADPUB.JSRI.9.2.179","DOIUrl":"https://doi.org/10.18869/ACADPUB.JSRI.9.2.179","url":null,"abstract":"Consider the problem of estimating true density, h(·) based upon a random sample X1, . . . , Xn. In general, h(·) is approximated using an appropriate (in some sense, see below) model fθ(x). This article using Vuong’s (1989) test along with a collection of k(> 2) non-nested models constructs a set of appropriate models, say model confidence set, for unknown model h(·). Application of such confidence set has been confirmed through a simulation study.","PeriodicalId":422124,"journal":{"name":"Journal of Statistical Research of Iran","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116469075","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 : 2013-03-15DOI: 10.18869/ACADPUB.JSRI.9.2.159
M. Sakizadeh, A. Gerami
Gupta and Shabbir (2008) have suggested an alternative form of ratio-type estimator for estimating the population mean. In this paper, we introduced new estimators by mixing two, stratified and cluster sampling method. Then we improved these estimators by using auxiliary variables and introducing new estimators. For sampling in infinite populations with a high geographic dispersion, the population will be divided into some smaller sub-population which leads to dispersion reduction to some extent. This will affect the variance of the estimator. Additionally dividing the population will result in saving cost, time and eases calculations.
{"title":"Some Improvment in the Estimation of Population Mean in Cluster Sampling","authors":"M. Sakizadeh, A. Gerami","doi":"10.18869/ACADPUB.JSRI.9.2.159","DOIUrl":"https://doi.org/10.18869/ACADPUB.JSRI.9.2.159","url":null,"abstract":"Gupta and Shabbir (2008) have suggested an alternative form of ratio-type estimator for estimating the population mean. In this paper, we introduced new estimators by mixing two, stratified and cluster sampling method. Then we improved these estimators by using auxiliary variables and introducing new estimators. For sampling in infinite populations with a high geographic dispersion, the population will be divided into some smaller sub-population which leads to dispersion reduction to some extent. This will affect the variance of the estimator. Additionally dividing the population will result in saving cost, time and eases calculations.","PeriodicalId":422124,"journal":{"name":"Journal of Statistical Research of Iran","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116268077","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 : 2013-03-15DOI: 10.18869/ACADPUB.JSRI.9.2.115
S. Baratpour, F. Khodadadi
Rayleigh distribution is widely used for life-time modeling and is important in electro vacuum devices and communication engineering. Rao et al. (2004) suggested the Cumulative Residual Entropy (CRE), which is the extension of the Shannon entropy to the the cumulative distribution function. In this paper, a general class of maximum CRE distributions is introduced and then we characterize the Rayleigh distribution and use it to construct a goodness-of-fit test for ascertaining appropriateness of such model. For constructing the test statistics, we use Cumulative residual Kullback-Leibler information (CKL) that was introduced by Baratpour and Habibi (2012). Critical values for various sample sizes determined by means of Monte Carlo simulations are presented for the test statistics. A Monte Carlo power analysis is performed for various alternatives and sample sizes in order to compare the proposed test with several existing goodness-of-fit tests based on the empirical distribution. We find that the proposed test has good power properties. The use of the proposed test is shown in an illustrative example.
{"title":"A Cumulative Residual Entropy Characterization of the Rayleigh Distribution and Related Goodness-of-Fit Test","authors":"S. Baratpour, F. Khodadadi","doi":"10.18869/ACADPUB.JSRI.9.2.115","DOIUrl":"https://doi.org/10.18869/ACADPUB.JSRI.9.2.115","url":null,"abstract":"Rayleigh distribution is widely used for life-time modeling and is important in electro vacuum devices and communication engineering. Rao et al. (2004) suggested the Cumulative Residual Entropy (CRE), which is the extension of the Shannon entropy to the the cumulative distribution function. In this paper, a general class of maximum CRE distributions is introduced and then we characterize the Rayleigh distribution and use it to construct a goodness-of-fit test for ascertaining appropriateness of such model. For constructing the test statistics, we use Cumulative residual Kullback-Leibler information (CKL) that was introduced by Baratpour and Habibi (2012). Critical values for various sample sizes determined by means of Monte Carlo simulations are presented for the test statistics. A Monte Carlo power analysis is performed for various alternatives and sample sizes in order to compare the proposed test with several existing goodness-of-fit tests based on the empirical distribution. We find that the proposed test has good power properties. The use of the proposed test is shown in an illustrative example.","PeriodicalId":422124,"journal":{"name":"Journal of Statistical Research of Iran","volume":"118 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120827466","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 : 2013-03-10DOI: 10.18869/ACADPUB.JSRI.9.2.133
Mona Shokripour, A. Mohammadpour, Mina Aminghafari
. In this article, we propose a new method for selecting level dependent threshold in wavelet shrinkage using the empirical Bayes framework. We employ both Bayesian and frequentist testing hypothesis instead of point estimation method. The best test yields the best prior and hence the more appropriate wavelet thresholds. The standard model functions are used to illustrate the performance of the proposed method and make comparisons with other traditional methods.
{"title":"Parametric Empirical Bayes Test and Its Application to Selection of Wavelet Threshold","authors":"Mona Shokripour, A. Mohammadpour, Mina Aminghafari","doi":"10.18869/ACADPUB.JSRI.9.2.133","DOIUrl":"https://doi.org/10.18869/ACADPUB.JSRI.9.2.133","url":null,"abstract":". In this article, we propose a new method for selecting level dependent threshold in wavelet shrinkage using the empirical Bayes framework. We employ both Bayesian and frequentist testing hypothesis instead of point estimation method. The best test yields the best prior and hence the more appropriate wavelet thresholds. The standard model functions are used to illustrate the performance of the proposed method and make comparisons with other traditional methods.","PeriodicalId":422124,"journal":{"name":"Journal of Statistical Research of Iran","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125533972","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 : 2013-03-01DOI: 10.18869/acadpub.jsri.9.2.147
A. Dolati, M. Karbasian
. Durante et al. (2007) introduced a class of bivariate copulas depending on two generators which generalizes some known families such as the Archimedean copulas. In this paper we provide some result on properties of this family when the generators are certain univariate survival functions. MSC 2010: 62H20, 60E15.
{"title":"Some Results on a Generalized Archimedean Family of Copulas","authors":"A. Dolati, M. Karbasian","doi":"10.18869/acadpub.jsri.9.2.147","DOIUrl":"https://doi.org/10.18869/acadpub.jsri.9.2.147","url":null,"abstract":". Durante et al. (2007) introduced a class of bivariate copulas depending on two generators which generalizes some known families such as the Archimedean copulas. In this paper we provide some result on properties of this family when the generators are certain univariate survival functions. MSC 2010: 62H20, 60E15.","PeriodicalId":422124,"journal":{"name":"Journal of Statistical Research of Iran","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121263056","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 : 2013-03-01DOI: 10.18869/ACADPUB.JSRI.9.2.195
K. Ahmadi, V. A. Khalaf, M. Rezaei
In this paper, we discuss the statistical inference on the unknown parameters and reliability function of type-II extreme value (EVII ) distribution when the observed data are progressively type-II censored. By applying EM algorithm, we obtain maximum likelihood estimates (MLEs). We also suggest approximate maximum likelihood estimators (AMLEs), which have explicit expressions. We provide Bayes estimates using both the symmetric and asymmetric loss functions via squared error loss, LINEX loss, and general entropy loss functions. Bayes estimates are obtained using the idea of Lindley and Markov chain Monte Carlo techniques. Finally, Monte Carlo simulations are presented to illustrate the methods discussed in this paper. Analysis is also carried out for a real data set.
{"title":"Estimation for the Type-II Extreme Value Distribution Based on Progressive Type-II Censoring","authors":"K. Ahmadi, V. A. Khalaf, M. Rezaei","doi":"10.18869/ACADPUB.JSRI.9.2.195","DOIUrl":"https://doi.org/10.18869/ACADPUB.JSRI.9.2.195","url":null,"abstract":"In this paper, we discuss the statistical inference on the unknown parameters and reliability function of type-II extreme value (EVII ) distribution when the observed data are progressively type-II censored. By applying EM algorithm, we obtain maximum likelihood estimates (MLEs). We also suggest approximate maximum likelihood estimators (AMLEs), which have explicit expressions. We provide Bayes estimates using both the symmetric and asymmetric loss functions via squared error loss, LINEX loss, and general entropy loss functions. Bayes estimates are obtained using the idea of Lindley and Markov chain Monte Carlo techniques. Finally, Monte Carlo simulations are presented to illustrate the methods discussed in this paper. Analysis is also carried out for a real data set.","PeriodicalId":422124,"journal":{"name":"Journal of Statistical Research of Iran","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128710361","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 : 2012-09-01DOI: 10.18869/acadpub.jsri.9.1.1
F. Z. Labbaf, H. Talebi
. The problem of obtaining the optimum design, which is able to discriminate between several rival models has been considered in this paper. We give an optimality-criterion, using a Bayesian approach. This is an exten-sion of the Bayesian KL-optimality to more than two models. A modification is made to deal with nested models. The proposed Bayesian optimality criterion is a weighted average, where the weights are corresponding probabilities of models to let them be true. We consider these probabilities coming from a Poisson distribution.
{"title":"Bayesian Optimum Design Criterion for Multi Models Discrimination","authors":"F. Z. Labbaf, H. Talebi","doi":"10.18869/acadpub.jsri.9.1.1","DOIUrl":"https://doi.org/10.18869/acadpub.jsri.9.1.1","url":null,"abstract":". The problem of obtaining the optimum design, which is able to discriminate between several rival models has been considered in this paper. We give an optimality-criterion, using a Bayesian approach. This is an exten-sion of the Bayesian KL-optimality to more than two models. A modification is made to deal with nested models. The proposed Bayesian optimality criterion is a weighted average, where the weights are corresponding probabilities of models to let them be true. We consider these probabilities coming from a Poisson distribution.","PeriodicalId":422124,"journal":{"name":"Journal of Statistical Research of Iran","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124829111","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 : 2012-03-23DOI: 10.18869/ACADPUB.JSRI.9.1.31
Maryam Baghery, F. Yousefzadeh
This paper, determines the confidence interval using the Fisher information under progressive type-II censoring for the k-step exponential step-stress accelerated life testing. We study the performance of these confidence intervals. Finally an example is given to illustrate the proposed procedures.
{"title":"Interval Estimation for the Exponential Distribution under Progressive Type-II Censored Step-Stress Accelerated Life-Testing Model Based on Fisher Information","authors":"Maryam Baghery, F. Yousefzadeh","doi":"10.18869/ACADPUB.JSRI.9.1.31","DOIUrl":"https://doi.org/10.18869/ACADPUB.JSRI.9.1.31","url":null,"abstract":"This paper, determines the confidence interval using the Fisher information under progressive type-II censoring for the k-step exponential step-stress accelerated life testing. We study the performance of these confidence intervals. Finally an example is given to illustrate the proposed procedures.","PeriodicalId":422124,"journal":{"name":"Journal of Statistical Research of Iran","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115043985","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 : 2012-03-23DOI: 10.18869/ACADPUB.JSRI.9.1.11
A. Asgharzadeh, R. Valiollahi
Abstract. In this paper, we discuss different predictors of times to failure of units censored in a hybrid censored sample from exponential distribution. Bayesian and non-Bayesian point predictors for the times to failure of units are obtained. Non-Bayesian prediction intervals are obtained based on pivotal and highest conditional density methods. Bayesian prediction intervals are also proposed. One real data set has been analyzed to illustrate all the prediction methods. Finally, different prediction methods have been compared using Monte Carlo simulations.
{"title":"Prediction of Times to Failure of Censored Units in Hybrid Censored Samples from Exponential Distribution","authors":"A. Asgharzadeh, R. Valiollahi","doi":"10.18869/ACADPUB.JSRI.9.1.11","DOIUrl":"https://doi.org/10.18869/ACADPUB.JSRI.9.1.11","url":null,"abstract":"Abstract. In this paper, we discuss different predictors of times to failure of units censored in a hybrid censored sample from exponential distribution. Bayesian and non-Bayesian point predictors for the times to failure of units are obtained. Non-Bayesian prediction intervals are obtained based on pivotal and highest conditional density methods. Bayesian prediction intervals are also proposed. One real data set has been analyzed to illustrate all the prediction methods. Finally, different prediction methods have been compared using Monte Carlo simulations.","PeriodicalId":422124,"journal":{"name":"Journal of Statistical Research of Iran","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129362502","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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