1
1735-1294
Statistical Research and Training Center - Statistical Centre of Iran
53
General
Efficient Estimation of the Density and Cumulative Distribution Function of the Generalized Rayleigh Distribution
Alizadeh
M.
Bagheri
F.
M. Khaleghy Moghaddam
M.
1
9
2013
10
1
1
22
21
12
2015
21
12
2015
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
52
General
Recurrence Relations for Quotient Moment of Generalized Pareto Distribution Based on Generalized Order Statistics and Characterization
Kumar
Devendra
1
9
2013
10
1
23
39
20
12
2015
20
12
2015
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.
54
General
Analysis of Record Data from the Scaled Logistic Distribution
Asgharzadeh
A.
Abdi
M.
valiollahi
R.
1
9
2013
10
1
41
62
21
12
2015
21
12
2015
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.
55
General
Plain Answers to Several Questions about Association/Independence Structure in Complete/Incomplete Contingency Tables
Ghoreishi
K.
Meshkani
R.
1
9
2013
10
1
63
84
21
12
2015
21
12
2015
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.
56
General
Exp-Uniform Distribution: Properties and Characterizations
Javanshiri
Z.
Habibi Rad
A.
G. Hamedani
H.
1
9
2013
10
1
85
106
21
12
2015
21
12
2015
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.
57
General
A Brief Determination of Certain Class of Power Semicircle Distribution
Roozegar
Rasool
Soltani
Reza
1
9
2013
10
1
107
111
21
12
2015
21
12
2015
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).