Pub Date : 2022-04-20DOI: 10.13052/jrss0974-8024.15110
Ranjita Pandey, Pulkit Srivastava
The present paper, discusses classical and Bayesian estimation of unknown combined parameters of two different log-logistic models with common shape parameters and different scale parameters under a new type of censoring scheme known as joint type II censoring scheme. Maximum likelihood estimators are derived. Bayes estimates of parameters are proposed under different loss functions. Classical asymptotic confidence intervals along with the Bayesian credible intervals and Highest Posterior Density region are also constructed. Markov Chain Monte Carlo approximation method is used for simulating the theoretic results. Comparative assessment of the classical and the Bayes results are illustrated through a real archived dataset.
{"title":"Bayesian Estimation for the Two Log-Logistic Models Under Joint Type II Censoring Schemes","authors":"Ranjita Pandey, Pulkit Srivastava","doi":"10.13052/jrss0974-8024.15110","DOIUrl":"https://doi.org/10.13052/jrss0974-8024.15110","url":null,"abstract":"The present paper, discusses classical and Bayesian estimation of unknown combined parameters of two different log-logistic models with common shape parameters and different scale parameters under a new type of censoring scheme known as joint type II censoring scheme. Maximum likelihood estimators are derived. Bayes estimates of parameters are proposed under different loss functions. Classical asymptotic confidence intervals along with the Bayesian credible intervals and Highest Posterior Density region are also constructed. Markov Chain Monte Carlo approximation method is used for simulating the theoretic results. Comparative assessment of the classical and the Bayes results are illustrated through a real archived dataset.","PeriodicalId":42526,"journal":{"name":"Journal of Reliability and Statistical Studies","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2022-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48786947","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}
This article establishes some improved classes of difference and ratio type estimators of population mean of study variable using information on auxiliary attribute under stratified simple random sampling. The usual mean estimator, classical ratio estimator, classical product estimator and classical regression estimator are identified as particular cases of the proposed classes of estimators for different values of the characterising scalars. The expression of mean square error of the suggested classes of estimators has been studied up to first order of approximation and their effective performances are likened with respect to the conventional as well as lately existing estimators. Subsequently, an empirical study has been carried out using a real data set in support of theoretical results. The empirical results justify the proposition of the proposed classes of estimators in terms of percent relative efficiency over all discussed work till date. Suitable suggestions are forwarded to the survey practitioners.
{"title":"On Some Improved Classes of Estimators Under Stratified Sampling Using Attribute","authors":"Shashi Bhushan, Anoop Kumar, Dushyant Tyagi, Saurabh Singh","doi":"10.13052/jrss0974-8024.1518","DOIUrl":"https://doi.org/10.13052/jrss0974-8024.1518","url":null,"abstract":"This article establishes some improved classes of difference and ratio type estimators of population mean of study variable using information on auxiliary attribute under stratified simple random sampling. The usual mean estimator, classical ratio estimator, classical product estimator and classical regression estimator are identified as particular cases of the proposed classes of estimators for different values of the characterising scalars. The expression of mean square error of the suggested classes of estimators has been studied up to first order of approximation and their effective performances are likened with respect to the conventional as well as lately existing estimators. Subsequently, an empirical study has been carried out using a real data set in support of theoretical results. The empirical results justify the proposition of the proposed classes of estimators in terms of percent relative efficiency over all discussed work till date. Suitable suggestions are forwarded to the survey practitioners.","PeriodicalId":42526,"journal":{"name":"Journal of Reliability and Statistical Studies","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2022-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48570738","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 : 2022-04-16DOI: 10.13052/jrss0974-8024.1519
Julia T. Thomas, Mahesh Kumar
Inventory management is the core of the supply chain management system, in which the economic order quantity (EOQ) model is a fundamental inventory model. This paper develops a fuzzy EOQ model in the presence of inspection errors in single sampling plans. The model assumes probability of mis-classifications. An inventory system is hypothesized where the orders undergo acceptance sampling, back-orders are eliminated, and defectives are set aside from the inventory. Due to the presence of vagueness in real time data, the rate at which an order turn to be scrap, the costs of holding, and the back-orders are characterized by fuzzy random variables. Since total profit involved is a random variable, maximum total expected profit is obtained. Some numerical examples are presented, and a sensitivity analysis study is carried out to check the validity of the model developed.
{"title":"Design of Fuzzy Economic Order Quantity (EOQ) Model in the Presence of Inspection Errors in Single Sampling Plans","authors":"Julia T. Thomas, Mahesh Kumar","doi":"10.13052/jrss0974-8024.1519","DOIUrl":"https://doi.org/10.13052/jrss0974-8024.1519","url":null,"abstract":"Inventory management is the core of the supply chain management system, in which the economic order quantity (EOQ) model is a fundamental inventory model. This paper develops a fuzzy EOQ model in the presence of inspection errors in single sampling plans. The model assumes probability of mis-classifications. An inventory system is hypothesized where the orders undergo acceptance sampling, back-orders are eliminated, and defectives are set aside from the inventory. Due to the presence of vagueness in real time data, the rate at which an order turn to be scrap, the costs of holding, and the back-orders are characterized by fuzzy random variables. Since total profit involved is a random variable, maximum total expected profit is obtained. Some numerical examples are presented, and a sensitivity analysis study is carried out to check the validity of the model developed.","PeriodicalId":42526,"journal":{"name":"Journal of Reliability and Statistical Studies","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2022-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43026298","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 : 2022-03-21DOI: 10.13052/jrss0974-8024.1517
Sumit Kumar
In this study, to estimate the process capability index Cpy when the process follows different distributions (Lindley, Xgamma, and Akash distribution), we have used five methods of estimation, namely, the maximum likelihood method of estimation, least and weighted least squares method of estimation, maximum product of spacings method of estimation and Bayesian method of estimation. The Bayesian estimation is studied for symmetric loss function with the help of the Metropolis-Hastings algorithm method. The confidence intervals for the index Cpy are constructed based on four bootstrap methods and Bayesian methods. We studied the performances of these estimators based on their corresponding MSEs/risks for the point estimates of Cpy, and average widths AW for interval estimates. To assess the accuracy of the various approaches, Monte Carlo simulations are conducted. It is found that the Bayes estimates performed better than the considered classical estimates in terms of their corresponding risks. To illustrate the performance of the proposed methods, two real data sets are analyzed.
{"title":"Classical and the Bayesian estimation of process capability index Cpy: A comparative study","authors":"Sumit Kumar","doi":"10.13052/jrss0974-8024.1517","DOIUrl":"https://doi.org/10.13052/jrss0974-8024.1517","url":null,"abstract":"In this study, to estimate the process capability index Cpy when the process follows different distributions (Lindley, Xgamma, and Akash distribution), we have used five methods of estimation, namely, the maximum likelihood method of estimation, least and weighted least squares method of estimation, maximum product of spacings method of estimation and Bayesian method of estimation. The Bayesian estimation is studied for symmetric loss function with the help of the Metropolis-Hastings algorithm method. The confidence intervals for the index Cpy are constructed based on four bootstrap methods and Bayesian methods. We studied the performances of these estimators based on their corresponding MSEs/risks for the point estimates of Cpy, and average widths AW for interval estimates. To assess the accuracy of the various approaches, Monte Carlo simulations are conducted. It is found that the Bayes estimates performed better than the considered classical estimates in terms of their corresponding risks. To illustrate the performance of the proposed methods, two real data sets are analyzed.","PeriodicalId":42526,"journal":{"name":"Journal of Reliability and Statistical Studies","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2022-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48295245","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 : 2022-02-22DOI: 10.13052/jrss0974-8024.1514
H. P. Singh, P. Nigam
In this paper we have suggested a generalized class of estimators for estimating the finite population mean Y¯Y¯ of the study variable y using information on two auxiliary variables x and z. We have studied the properties of the proposed generalized class of estimators in simple random sampling without replacement scheme and in stratified random sampling up to the first order of approximation. It is shown that the suggested class of estimators is more efficient than the conventional unbiased estimator, ratio estimator, product estimator, traditional difference estimator, Srivastava (1967) estimator, Ray et al. (1979) estimator, Vos (1980) estimator, Upadhyaya et al. (1985) estimator, Rao (1991) estimator and Gupta and Shabbir (2008) estimator. Theoretical results are well supported through an empirical study.
{"title":"A Generalized Class of Estimators for Finite Population Mean Using Two Auxiliary Variables in Sample Surveys","authors":"H. P. Singh, P. Nigam","doi":"10.13052/jrss0974-8024.1514","DOIUrl":"https://doi.org/10.13052/jrss0974-8024.1514","url":null,"abstract":"In this paper we have suggested a generalized class of estimators for estimating the finite population mean Y¯Y¯ of the study variable y using information on two auxiliary variables x and z. We have studied the properties of the proposed generalized class of estimators in simple random sampling without replacement scheme and in stratified random sampling up to the first order of approximation. It is shown that the suggested class of estimators is more efficient than the conventional unbiased estimator, ratio estimator, product estimator, traditional difference estimator, Srivastava (1967) estimator, Ray et al. (1979) estimator, Vos (1980) estimator, Upadhyaya et al. (1985) estimator, Rao (1991) estimator and Gupta and Shabbir (2008) estimator. Theoretical results are well supported through an empirical study.","PeriodicalId":42526,"journal":{"name":"Journal of Reliability and Statistical Studies","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2022-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44371185","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 : 2022-02-14DOI: 10.13052/jrss0974-8024.1513
M. Jeelani, F. Danish, Saquib Khan
In this investigation, various statistical models were fitted on simulated symmetric and asymmetric data. Fitting of models was carried out with the help of various libraries in R studio, and various selection criteria were also used while fitting of models. In order to evaluate different validation techniques the simulated data was divided in training and testing data set and various functions in R were developed for the purpose of validation. Coefficient summary revealed that all statistical models were statistically significant across both symmetric as well as asymmetric distributions. In preliminary analysis TFEM (Type First Exponential Model) was found out to be the best linear model across both symmetric and asymmetric distributions with lower values of RMSE, MAE, BIAS, AIC and BIC. Among non-linear models, Haung model was found out to be best model across both the distributions as it has lower values of RMSE, MAE etc. Different validation techniques were used in the present study. Lower rates of prediction error in comparison to its counter parts, 5-folded cross validation performed better across all the statistical models.
在本研究中,对模拟对称和非对称数据进行了各种统计模型的拟合。模型的拟合是借助R studio中的各种库进行的,模型的拟合也使用了各种选择标准。为了评估不同的验证技术,将模拟数据分为训练数据集和测试数据集,并在R中开发了各种用于验证的函数。系数总结显示,所有统计模型在对称分布和非对称分布中都具有统计学显著性。初步分析发现,在对称分布和非对称分布中,TFEM (Type First Exponential Model)是最佳的线性模型,RMSE、MAE、BIAS、AIC和BIC值都较低。在非线性模型中,Haung模型具有较低的RMSE、MAE等值,是两种分布下的最佳模型。在本研究中使用了不同的验证技术。预测错误率较低,5折交叉验证在所有统计模型中表现更好。
{"title":"Predictive Modelling: An Assessment Through Validation Techniques","authors":"M. Jeelani, F. Danish, Saquib Khan","doi":"10.13052/jrss0974-8024.1513","DOIUrl":"https://doi.org/10.13052/jrss0974-8024.1513","url":null,"abstract":"In this investigation, various statistical models were fitted on simulated symmetric and asymmetric data. Fitting of models was carried out with the help of various libraries in R studio, and various selection criteria were also used while fitting of models. In order to evaluate different validation techniques the simulated data was divided in training and testing data set and various functions in R were developed for the purpose of validation. Coefficient summary revealed that all statistical models were statistically significant across both symmetric as well as asymmetric distributions. In preliminary analysis TFEM (Type First Exponential Model) was found out to be the best linear model across both symmetric and asymmetric distributions with lower values of RMSE, MAE, BIAS, AIC and BIC. Among non-linear models, Haung model was found out to be best model across both the distributions as it has lower values of RMSE, MAE etc. Different validation techniques were used in the present study. Lower rates of prediction error in comparison to its counter parts, 5-folded cross validation performed better across all the statistical models.","PeriodicalId":42526,"journal":{"name":"Journal of Reliability and Statistical Studies","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2022-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46137928","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 : 2022-02-04DOI: 10.13052/jrss0974-8024.1512
M. Dube, Subhash Kr. Yadav, Vishwajeet P. Singh
In developmental studies, the infrastructural sector is considered as an important component of overall economic development. The infrastructural growth in the state of Uttar Pradesh is undoubtedly critical since independence. The main focus of this paper is to uncover the principal factors or dimensions of infrastructural characteristics and to quantify the level of infrastructural development of Uttar Pradesh into five clusters having different grade of development using Exploratory Factor Analysis & K-means Cluster Analysis. The analysis has been carried out by taking into account various infrastructural indicators for the time period of two years from 2018 to 2019. The results of the present analysis led to the identification of the five factors of infrastructural characteristics, and the classification of all the seventy-five districts of Uttar Pradesh into five regions with different degree of infrastructural development. The ‘infrastructural regions’ uncovered through this procedure allow a much more useful characterization of Uttar Pradesh for the policy making purpose. The same technique may be applied to the whole country and other countries as well.
{"title":"Uncovering Regional Disparities in Infrastructural Development of Uttar Pradesh: An Exploratory Factor Analysis","authors":"M. Dube, Subhash Kr. Yadav, Vishwajeet P. Singh","doi":"10.13052/jrss0974-8024.1512","DOIUrl":"https://doi.org/10.13052/jrss0974-8024.1512","url":null,"abstract":"In developmental studies, the infrastructural sector is considered as an important component of overall economic development. The infrastructural growth in the state of Uttar Pradesh is undoubtedly critical since independence. The main focus of this paper is to uncover the principal factors or dimensions of infrastructural characteristics and to quantify the level of infrastructural development of Uttar Pradesh into five clusters having different grade of development using Exploratory Factor Analysis & K-means Cluster Analysis. The analysis has been carried out by taking into account various infrastructural indicators for the time period of two years from 2018 to 2019. The results of the present analysis led to the identification of the five factors of infrastructural characteristics, and the classification of all the seventy-five districts of Uttar Pradesh into five regions with different degree of infrastructural development. The ‘infrastructural regions’ uncovered through this procedure allow a much more useful characterization of Uttar Pradesh for the policy making purpose. The same technique may be applied to the whole country and other countries as well.","PeriodicalId":42526,"journal":{"name":"Journal of Reliability and Statistical Studies","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2022-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42846843","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 : 2022-02-04DOI: 10.13052/jrss0974-8024.1511
A. Singh, V. K. Singh
We have defined a class of estimators for population mean under non-response error based upon the concept of sub-sampling of non-respondents utilizing an auxiliary variable. The class is a one-parameter class of estimators which is based on the idea of exponential type estimators (ETE). The model biasness and model-mean square error of the class and some of its important members have been derived under polynomial regression model (PRM). The effect of variations in PRM specifications on the efficiency of the estimators has been discussed based upon the empirical results.
{"title":"A Family of Estimators for Population Mean Under Model Approach in Presence of Non-Response","authors":"A. Singh, V. K. Singh","doi":"10.13052/jrss0974-8024.1511","DOIUrl":"https://doi.org/10.13052/jrss0974-8024.1511","url":null,"abstract":"We have defined a class of estimators for population mean under non-response error based upon the concept of sub-sampling of non-respondents utilizing an auxiliary variable. The class is a one-parameter class of estimators which is based on the idea of exponential type estimators (ETE). The model biasness and model-mean square error of the class and some of its important members have been derived under polynomial regression model (PRM). The effect of variations in PRM specifications on the efficiency of the estimators has been discussed based upon the empirical results.","PeriodicalId":42526,"journal":{"name":"Journal of Reliability and Statistical Studies","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2022-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44885203","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 : 2021-12-14DOI: 10.13052/10.13052/jrss0974-8024.14215
A. Yadav, Mahendra Saha, Shivanshi Shukla, Harsh Tripathi, Rajashree Dey
In this article, a reliability test plan is developed for Logistic-exponential distribution (LoED) under time truncated life test scheme. The distribution has been chosen because it can used to model lifetime of several reliability phenomenon and it performs better than many well known existing distributions. With the discussions of statistical properties of the aforesaid model, the reliability test plan has been established under the assumption of median quality characteristics when minimum confidence level P* is given. To quench the objective of the paper i.e; to serve as a guiding aid to the emerging practitioners, minimum sample sizes have been obtained by using binomial approximation and Poisson approximation for the proposed plan. Further, operating characteristic (OC) values for the various choices of quality level are placed. Also, minimum ratio of true median life to specified life has been presented for specified producer’s risk. Important findings of the proposed reliability test plan are given for considered value of k=0.75,1,2. To demonstrate the appropriateness of suggested reliability test plan is achieved using four real life situation.
{"title":"Reliability Test Plan Based on Logistic-Exponential Distribution and Its Application","authors":"A. Yadav, Mahendra Saha, Shivanshi Shukla, Harsh Tripathi, Rajashree Dey","doi":"10.13052/10.13052/jrss0974-8024.14215","DOIUrl":"https://doi.org/10.13052/10.13052/jrss0974-8024.14215","url":null,"abstract":"In this article, a reliability test plan is developed for Logistic-exponential distribution (LoED) under time truncated life test scheme. The distribution has been chosen because it can used to model lifetime of several reliability phenomenon and it performs better than many well known existing distributions. With the discussions of statistical properties of the aforesaid model, the reliability test plan has been established under the assumption of median quality characteristics when minimum confidence level P* is given. To quench the objective of the paper i.e; to serve as a guiding aid to the emerging practitioners, minimum sample sizes have been obtained by using binomial approximation and Poisson approximation for the proposed plan. Further, operating characteristic (OC) values for the various choices of quality level are placed. Also, minimum ratio of true median life to specified life has been presented for specified producer’s risk. Important findings of the proposed reliability test plan are given for considered value of k=0.75,1,2. To demonstrate the appropriateness of suggested reliability test plan is achieved using four real life situation.","PeriodicalId":42526,"journal":{"name":"Journal of Reliability and Statistical Studies","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46210016","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 : 2021-12-06DOI: 10.13052/10.13052/jrss0974-8024.14212
H. Muhammed, E. A. Muhammed
In this paper, Bayesian and non-Bayesian estimation of the inverted Topp-Leone distribution shape parameter are studied when the sample is complete and random censored. The maximum likelihood estimator (MLE) and Bayes estimator of the unknown parameter are proposed. The Bayes estimates (BEs) have been computed based on the squared error loss (SEL) function and using Markov Chain Monte Carlo (MCMC) techniques. The asymptotic, bootstrap (p,t), and highest posterior density intervals are computed. The Metropolis Hasting algorithm is proposed for Bayes estimates. Monte Carlo simulation is performed to compare the performances of the proposed methods and one real data set has been analyzed for illustrative purposes.
{"title":"Inverted Topp-Leone Distribution: Contribution to a Family of J-Shaped Frequency Functions in Presence of Random Censoring","authors":"H. Muhammed, E. A. Muhammed","doi":"10.13052/10.13052/jrss0974-8024.14212","DOIUrl":"https://doi.org/10.13052/10.13052/jrss0974-8024.14212","url":null,"abstract":"In this paper, Bayesian and non-Bayesian estimation of the inverted Topp-Leone distribution shape parameter are studied when the sample is complete and random censored. The maximum likelihood estimator (MLE) and Bayes estimator of the unknown parameter are proposed. The Bayes estimates (BEs) have been computed based on the squared error loss (SEL) function and using Markov Chain Monte Carlo (MCMC) techniques. The asymptotic, bootstrap (p,t), and highest posterior density intervals are computed. The Metropolis Hasting algorithm is proposed for Bayes estimates. Monte Carlo simulation is performed to compare the performances of the proposed methods and one real data set has been analyzed for illustrative purposes.","PeriodicalId":42526,"journal":{"name":"Journal of Reliability and Statistical Studies","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2021-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47680804","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}