Journal of Statistical Theory and Applications

ISSN: 1538-7887
Volume 15, Issue 4, December 2016
Mahmoud M. Mansour, Mohammad Ahsanullah, Zohdy M. Nofal, Omar H. Khalaf
Pages: 313 - 325
In this Paper, a new four-parameter distribution motivated mainly by dealing with series-parallel system is introduced. Moments, conditional moments and moment generating function of the new distribution including are presented. Estimation of its parameters is studied. characterization of the new model...
Ahmed Z. Afify, Haitham M. Yousof, G.G. Hamedani, Gokarna R. Aryal
Pages: 326 - 344
A new generalization of the Weibull-Pareto distribution called the exponentiated Weibull-Pareto distribution is defined and studied. Various structural properties including ordinary moments, quantiles, R´enyi and q-entropies and order statistics are derived. We proposed the method of maximum likelihood...
Omar M. Bdair, Mohammad Z. Raqab
Pages: 345 - 366
Based on record data, prediction of the future records from the two-parameter Weibull distribution is studied. First we consider the sampling based procedure to compute the Bayes estimates and also to construct symmetric credible intervals. Secondly, we consider one-sequence and two-sequence Bayes...
Sayed Jamal Mirkamali, Mojtaba Ganjali
Pages: 373 - 386
This paper proposes a Bayesian approach for the analysis of mixed correlated nominal, ordinal and continuous outcomes with possibility of missing values using a variation of Markov Chain Monte Carlo (MCMC) method named Parameter Expanded and Reparamerized Metropolis Hastings (PX-RPMH) method. A general...
Muhammad Akram, M. Ishaq Bhatti, Muhammad Ashfaq, Asif Ali Khan
Pages: 387 - 399
This paper uses various forecasting methods to forecast future crop production levels using time series data for four major crops in Pakistan: wheat, rice, cotton and pulses. These different forecasting methods are then assessed based on their out-of-sample forecast accuracies. We empirically compare...
Rahul Bhattacharya
Pages: 400 - 404
For testing a simple null hypothesis against a simple alternative using Neyman-Pearson theory, examples of most powerful non-randomized critical regions are constructed, which are overlapping for varying sizes. A likelihood ratio based criterion, characterizing such critical regions, is also provided....
S. Hossain, M. Ghahramani
Pages: 405 - 423
This paper introduces shrinkage estimators for the parameter vector of a linear regression model with con- ditionally heteroscedastic errors such as the class of generalized autoregressive conditional heteroscedastic (GARCH) errors when some of the regression parameters are restricted to a subspace....