Journal of Statistical Research of Iran
http://jsri.srtc.ac.ir
Journal of Statistical Research of Iran JSRI - Journal articles for year 2013, Volume 10, Number 1Yektaweb Collection - http://www.yektaweb.comen2013/9/10Efficient Estimation of the Density and Cumulative Distribution Function of the Generalized Rayleigh Distribution
http://jsri.srtc.ac.ir/browse.php?a_id=53&sid=1&slc_lang=en
<p>The uniformly minimum variance unbiased (UMVU), maximum likelihood, percentile (PC), least squares (LS) and weighted least squares (WLS) estimators of the probability density function (pdf) and cumulative distribution function are derived for the generalized Rayleigh distribution. This model can be used quite effectively in modelling strength data and also modeling general lifetime data. It has been shown that MLE is better than UMVUE and UMVUE is better than the others. An application to waiting times (min) of 100 bank customers</p>
M. AlizadehRecurrence Relations for Quotient Moment of Generalized Pareto Distribution Based on Generalized Order Statistics and Characterization
http://jsri.srtc.ac.ir/browse.php?a_id=52&sid=1&slc_lang=en
<p>Generalized Pareto distribution play an important role in reliability, extreme value theory, and other branches of applied probability and statistics. This family of distributions includes exponential distribution, Pareto distribution, and Power distribution. In this paper, we established exact expressions and recurrence relations satisfied by the quotient moments of generalized order statistics for a generalized Pareto distribution. Further the results for quotient moments of order statistics and records are deduced from the relations obtained and a theorem for characterizing this distribution is presented.</p>
Devendra KumarAnalysis of Record Data from the Scaled Logistic Distribution
http://jsri.srtc.ac.ir/browse.php?a_id=54&sid=1&slc_lang=en
<p>In this paper, we consider the estimation of the unknown parameter of the scaled logistic distribution on the basis of record values. The maximum likelihood method does not provide an explicit estimator for the scale parameter. In this article, we present a simple method of deriving an explicit estimator by approximating the likelihood function. Bayes estimator is obtained using importance sampling. Asymptotic confidence intervals, bootstrap confidence interval and credible interval are also proposed. Monte Carlo simulations are performed to compare the different proposed methods. Analysis of one real data set is also given for illustrative purposes.</p>
<p></p>
A. AsgharzadehPlain Answers to Several Questions about Association/Independence Structure in Complete/Incomplete Contingency Tables
http://jsri.srtc.ac.ir/browse.php?a_id=55&sid=1&slc_lang=en
<p>In this paper, we develop some results based on Relational model (Klimova, et al. 2012) which permits a decomposition of logarithm of expected cell frequencies under a log-linear type model. These results imply plain answers to several questions in the context of analyzing of contingency tables. Moreover, determination of design matrix and hypothesis-induced matrix of the model will be discussed. Properties of maximum likelihood estimators of the model parameters are obtained. Some new model residuals and an alternative symmetric chi-square criterion are given. Two real examples illustrate the method.</p>
<p></p>
K. GhoreishiExp-Uniform Distribution: Properties and Characterizations
http://jsri.srtc.ac.ir/browse.php?a_id=56&sid=1&slc_lang=en
<p>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 characterizations 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.</p>
A. Habibi RadA Brief Determination of Certain Class of Power Semicircle Distribution
http://jsri.srtc.ac.ir/browse.php?a_id=57&sid=1&slc_lang=en
<p>In this paper, we give a new and direct proof for the recently proved conjecture raised in Soltani and Roozegar (2012). The conjecture can be proved in a few lines via the integral representation of the Gauss-hypergeometric function unlike the long proof in Roozegar and Soltani (2013).</p>
Rasool Roozegar