Advances in Statistics
http://www.i-scholar.in/index.php/Adst
<p>Advances in Statistics is a peer-reviewed, open access journal that publishes original research articles as well as review articles in all areas of statistics.</p><p> </p>en-USas@hindawi.com (Dr. Mohammmad Fraiwan Al-Saleh)as@hindawi.com (Dr. Mohammmad Fraiwan Al-Saleh)Thu, 28 Apr 2016 05:01:24 +0000OJS 2.4.2.0http://blogs.law.harvard.edu/tech/rss60Estimation in Step-Stress Accelerated Life Tests for Power Generalized Weibull Distribution with Progressive Censoring
http://www.i-scholar.in/index.php/Adst/article/view/98193
Based on progressive censoring, step-stress partially accelerated life tests are considered when the lifetime of a product follows power generalized Weibull distribution. The maximum likelihood estimates (MLEs) and Bayes estimates (BEs) are obtained for the distribution parameters and the acceleration factor. In addition, the approximate and bootstrap confidence intervals (CIs) of the estimators are presented. Furthermore, the optimal stress change time for the step-stress partially accelerated life test is determined by minimizing the asymptotic variance of MLEs of themodel parameters and the acceleration factor. Simulation results are carried out to study the precision of the MLEs and BEs for the parameters involved.M. M. Mohie EL-Din, S. E. Abu-Youssef, Nahed S. A. Ali, A. M. Abd El-Raheemhttp://www.i-scholar.in/index.php/Adst/article/view/98193Statistical Inference in Dependent Component Hybrid Systems with Masked Data
http://www.i-scholar.in/index.php/Adst/article/view/98194
Complex systems are usually composed of simple hybrid systems. In this paper,we consider statistical inference for two fundamental hybrid systems: series-parallel and parallel-series systems based on masked data. Assuming dependent lifetimes of components modelled by Marshall and Olkin's bivariate exponential distribution in the system, we present maximum likelihood and interval estimation of parameters of interest. Intensive simulation studies are performed to demonstrate the efficiency of the methods.Naijun Sha, Ronghua Wang, Ping Hu, Xiaoling Xuhttp://www.i-scholar.in/index.php/Adst/article/view/98194Relative Entropies and Jensen Divergences in the Classical Limit
http://www.i-scholar.in/index.php/Adst/article/view/98196
Metrics and distances in probability spaces have shown to be useful tools for physical purposes. Here we use this idea, with emphasis on Jensen Divergences and relative entropies, to investigate features of the road towards the classical limit. A well-known semiclassical model is used and recourse is made to numerical techniques, via the well-known Bandt and Pompe methodology, to extract probability distributions from the pertinent time-series associated with dynamical data.A. M. Kowalski, A. Plastinohttp://www.i-scholar.in/index.php/Adst/article/view/98196Estimation of the Derivatives of a Function in a Convolution Regression Model with Random Design
http://www.i-scholar.in/index.php/Adst/article/view/98198
A convolution regression model with random design is considered. We investigate the estimation of the derivatives of an unknown function, element of the convolution product. We introduce new estimators based on wavelet methods and provide theoretical guarantees on their good performances.Christophe Chesneau, Maher Kachourhttp://www.i-scholar.in/index.php/Adst/article/view/98198Bayesian Estimation of Inequality and Poverty Indices in Case of Pareto Distribution Using Different Priors under LINEX Loss Function
http://www.i-scholar.in/index.php/Adst/article/view/98200
Bayesian estimators of Gini index and a Poverty measure are obtained in case of Pareto distribution under censored and complete setup. The said estimators are obtained using two noninformative priors, namely, uniform prior and Jeffreys' prior, and one conjugate prior under the assumption of Linear Exponential (LINEX) loss function. Using simulation techniques, the relative efficiency of proposed estimators using different priors and loss functions is obtained. The performances of the proposed estimators have been compared on the basis of their simulated risks obtained under LINEX loss function.Kamaljit Kaur, Sangeeta Arora, Kalpana K. Mahajanhttp://www.i-scholar.in/index.php/Adst/article/view/98200