scholarly journals ON RELATIONS FOR QUOTIENT MOMENTS OF THE GENERALIZED PARETO DISTRIBUTION BASED ON RECORD VALUES AND A CHARACTERIZATION

2013 ◽  
Vol 31 (3_4) ◽  
pp. 327-336
Author(s):  
Devendra Kumar
Keyword(s):  
Pareto Distribution ◽  
Generalized Pareto Distribution ◽  
Record Values ◽  
Generalized Pareto

Inference on P(Y

2020 ◽  
Vol 72 (2) ◽  
pp. 89-110
Author(s):  
Manoj Chacko ◽  
Shiny Mathew
Keyword(s):  
Maximum Likelihood ◽  
Pareto Distribution ◽  
Generalized Pareto Distribution ◽  
Maximum Likelihood Estimators ◽  
Record Values ◽  
Asymptotic Distributions ◽  
Bayes Estimators ◽  
Generalized Pareto ◽  
Pareto Distributions ◽  
Generalized Pareto Distributions

In this article, the estimation of [Formula: see text] is considered when [Formula: see text] and [Formula: see text] are two independent generalized Pareto distributions. The maximum likelihood estimators and Bayes estimators of [Formula: see text] are obtained based on record values. The Asymptotic distributions are also obtained together with the corresponding confidence interval of [Formula: see text]. AMS 2000 subject classification: 90B25

scholarly journals Exact Moments of Generalized Pareto Distribution based on Generalized Order Statistics and Characterizations

2021 ◽  
pp. 213-226
Author(s):  
Bavita Singh ◽  
Rafiqullah Khan ◽  
Mohammad Azam Khan
Keyword(s):  
Order Statistics ◽  
Pareto Distribution ◽  
Generalized Pareto Distribution ◽  
Record Values ◽  
Generalized Order Statistics ◽  
Product Moments ◽  
Generalized Pareto ◽  
Mean And Variance ◽  
The Mean ◽  
Generalized Order

In this paper, we present simple explicit expressions for single and product moments of generalized order statistics from generalized Pareto distribution. These relations are deduced for the moments of order statistics and record values and tabulated the mean and variance of this distribution. Further, conditional expectation, recurrence relations for single as well as for product moments of generalized order statistics and truncated moment are used to characterize this distribution.

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