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Physical Sciences and Mathematics Commons™
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Articles 1 - 7 of 7
Full-Text Articles in Physical Sciences and Mathematics
Simple Unequal Allocation Procedure For Ranked Set Sampling With Skew Distributions, Dinesh Bhoj, Girish Chandra
Simple Unequal Allocation Procedure For Ranked Set Sampling With Skew Distributions, Dinesh Bhoj, Girish Chandra
Journal of Modern Applied Statistical Methods
A practical unbalanced Ranked Set Sampling (RSS) model is proposed to estimate the population mean of positively skewed distributions. The gains in the relative precisions of the population mean based on the proposed model for chosen distributions are uniformly higher than those based on balanced RSS and the t-model proposed in Kaur et al. (1997). The relative precisions of the simple unequal allocation model are, with one exception, better than (s, t)-model which is better than t-model. The relative precision of the proposed model is very close or equal to the optimal Neyman allocation model.
Simple Unbalanced Ranked Set Sampling For Mean Estimation Of Response Variable Of Developmental Programs, Girish Chandra, Dinesh S. Bhoj, Rajiv Pandey
Simple Unbalanced Ranked Set Sampling For Mean Estimation Of Response Variable Of Developmental Programs, Girish Chandra, Dinesh S. Bhoj, Rajiv Pandey
Journal of Modern Applied Statistical Methods
An unbalanced ranked set sampling (RSS) procedure on the skewed survey variable is proposed to estimate the population mean of a response variable from the area of developmental programs which are generally implemented under different phases. It is based on the unbalanced RSS under linear impacts of the program and is compared with the estimators based on simple random sampling (SRS) and balanced RSS. It is shown that the relative precision of the proposed estimator is higher than those of the estimators based on SRS and balanced RSS for three chosen skewed distributions of survey variables.
A Bivariate Distribution With Conditional Gamma And Its Multivariate Form, Sumen Sen, Rajan Lamichhane, Norou Diawara
A Bivariate Distribution With Conditional Gamma And Its Multivariate Form, Sumen Sen, Rajan Lamichhane, Norou Diawara
Journal of Modern Applied Statistical Methods
A bivariate distribution whose marginal are gamma and beta prime distribution is introduced. The distribution is derived and the generation of such bivariate sample is shown. Extension of the results are given in the multivariate case under a joint independent component analysis method. Simulated applications are given and they show consistency of our approach. Estimation procedures for the bivariate case are provided.
On The Properties Of Beta-Gamma Distribution, Lingji Kong, Carl Lee, J.H. Sepanski
On The Properties Of Beta-Gamma Distribution, Lingji Kong, Carl Lee, J.H. Sepanski
Journal of Modern Applied Statistical Methods
A class of generalized gamma distribution called the beta-gamma distribution is proposed. Some of its properties are examined. Its shape can be reversed J-shaped, unimodal, or bimodal. Reliability and hazard functions are also derived, and applications are discussed.
Analysis Of Type-Ii Progressively Hybrid Censored Competing Risks Data, Debasis Kundu, Avijit Joarder
Analysis Of Type-Ii Progressively Hybrid Censored Competing Risks Data, Debasis Kundu, Avijit Joarder
Journal of Modern Applied Statistical Methods
A Type-II progressively hybrid censoring scheme for competing risks data is introduced, where the experiment terminates at a pre-specified time. The likelihood inference of the unknown parameters is derived under the assumptions that the lifetime distributions of the different causes are independent and exponentially distributed. The maximum likelihood estimators of the unknown parameters are obtained in exact forms. Asymptotic confidence intervals and two bootstrap confidence intervals are also proposed. Bayes estimates and credible intervals of the unknown parameters are obtained under the assumption of gamma priors on the unknown parameters. Different methods have been compared using Monte Carlo simulations. One …
Large Sample And Bootstrap Intervals For The Gamma Scale Parameter Based On Grouped Data, Ayman Baklizi, Amjad Al-Nasser
Large Sample And Bootstrap Intervals For The Gamma Scale Parameter Based On Grouped Data, Ayman Baklizi, Amjad Al-Nasser
Journal of Modern Applied Statistical Methods
Interval estimation of the scale parameter of the gamma distribution using grouped data is considered in this article. Exact intervals do not exist and approximate intervals are needed Recently, Chen and Mi (2001) proposed alternative approximate intervals. In this article, some bootstrap and jackknife type intervals are proposed. The performance of these intervals is investigated and compared. The results show that some of the suggested intervals have a satisfactory statistical performance in situations where the sample size is small with heavy proportion of censoring.
Statistical Model And Estimation Of The Optimum Price For A Chain Of Price Setting Firms, Chengjie Xiong, Kejun Zhu
Statistical Model And Estimation Of The Optimum Price For A Chain Of Price Setting Firms, Chengjie Xiong, Kejun Zhu
Journal of Modern Applied Statistical Methods
A stochastic approach is used to model the economics of a chain of price setting firms. It is assumed that these firms have fixed capacities in their products, but random demands for their products. The optimum price, the optimum revenue, and the expected marginal revenue at a given price are investigated. The method of maximum likelihood is used to provide both point and confidence interval estimates. The coverage probabilities of confidence interval estimates based on a simulation study are presented.