scholarly journals Inference for generalized exponential distribution based on generalized order statistics

2015 ◽  
Vol 4 (2) ◽  
pp. 370
Author(s):  
Eldesoky Afify
Keyword(s):  
Order Statistics ◽  
Exponential Distribution ◽  
Survival Function ◽  
Simulated Data ◽  
Record Values ◽  
Generalized Order Statistics ◽  
Generalized Exponential Distribution ◽  
Upper Record Values ◽  
Upper Record ◽  
Generalized Order

<p>Estimation of a parameter of generalized exponential distribution (gexp) is obtained based on generalized order statistics. The maximum likelihood and Bayes methods are used for this purpose. Survival function and hazard rate are also computed. Estimation based on upper record values from generalized exponential distribution is obtained as a special case and compared by simulated data.</p>

scholarly journals Nonparametric Prediction Intervals of generalized order statistics from two independent sequences

2016 ◽  
Vol 4 (1) ◽  
pp. 36 ◽  
Author(s):  
Mostafa Mohie El-Din ◽  
Walid Emam
Keyword(s):  
Order Statistics ◽  
Record Values ◽  
Prediction Intervals ◽  
Generalized Order Statistics ◽  
Special Cases ◽  
Upper Record Values ◽  
Upper Record ◽  
Nonparametric Prediction ◽  
Nonparametric Prediction Intervals ◽  
Generalized Order

<p>This paper, discusses the problem of predicting future a generalized order statistic of an iid sequence sample was drawn from an arbitrary unknown distribution, based on observed also generalized order statistics from the same population. The coverage probabilities of these prediction intervals are exact and free of the parent distribution F(). Prediction formulas of ordinary order statistics and upper record values are extracted as special cases from the productive results. Finally, numerical computations on several models of ordered random variables are given to illustrate the proposed procedures.</p>

scholarly journals Bayesian Estimation of Stress Strength Reliability using Upper Record Values from Generalised Inverted Exponential Distribution

2019 ◽  
Vol 4 (4) ◽  
pp. 882-894
Author(s):  
Ritu Kumari ◽  
Kalpana K. Mahajan ◽  
Sangeeta Arora
Keyword(s):  
Exponential Distribution ◽  
Simulated Data ◽  
Record Values ◽  
Data Sets ◽  
Bayes Estimators ◽  
Informative Prior ◽  
Upper Record Values ◽  
Upper Record ◽  
Hpd Intervals ◽  
Simulated Data Sets

The paper develops Bayesian estimators and HPD intervals for the stress strength reliability of generalised inverted exponential distribution using upper record values. For prior distribution, informative prior as well as non-informative prior both are considered. The Bayes estimators are obtained under both symmetric and asymmetric loss functions. A simulation study is conducted to obtain the Bayes estimates of stress strength reliability. Simulated data sets are also considered here for illustration purpose.

scholarly journals Some Characterizations of the Distribution of the Condition Number of a Complex Gaussian Matrix

2020 ◽  
Vol 8 (1) ◽  
pp. 22-35
Author(s):  
M. Shakil ◽  
M. Ahsanullah
Keyword(s):  
Order Statistics ◽  
Condition Number ◽  
Record Values ◽  
Distributional Properties ◽  
Upper Record Values ◽  
Upper Record

AbstractThe objective of this paper is to characterize the distribution of the condition number of a complex Gaussian matrix. Several new distributional properties of the distribution of the condition number of a complex Gaussian matrix are given. Based on such distributional properties, some characterizations of the distribution are given by truncated moment, order statistics and upper record values.

scholarly journals Relations for Moments of Generalized Order Statistics for Transmuted Exponential Distribution and Characterization

2021 ◽  
pp. 43-50
Author(s):  
Saman Shahbaz ◽  
Mashail Al-Sobhi ◽  
Rehan Ahmad Khan Sherwani
Keyword(s):  
Order Statistics ◽  
Exponential Distribution ◽  
Generalized Order Statistics ◽  
Product Moments ◽  
Recursive Computation ◽  
Single And Product Moments ◽  
Generalized Order

The relations for moments of generalized order statistics (gos) for transmuted exponential distribution are obtained. These include relations for single, inverse, product and ratio moments. These relations are useful in for recursive computation of moments of gos for transmuted exponential distribution. Some characterizations of the distribution, based on single and product moments of gos, are also obtained.

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