scholarly journals The Moment Properties of Order, Reversed Order and Upper Record Statistics for the Power Ailamujia Distribution

2021 ◽  
Vol 20 ◽  
pp. 606-613
Author(s):  
Farrukh Jamal ◽  
Christophe Chesneau
Keyword(s):  
Order Statistics ◽  
Product Moments ◽  
Joint Distributions ◽  
Single Moments ◽  
Record Statistics ◽  
Upper Record ◽  
The Moment ◽  
Reversed Order ◽  
Single And Product Moments

The power Ailamujia distribution has been successfully developed in statistics, both theoretically and practically, performing well in the fitting of various types of data. This paper investigates the moment properties of the associated order, reversed order and upper record statistics, which are indeed unexplored aspects of this distribution. In particular, the exact expressions for the single moments of the order and reversed order statistics are provided. Some recurrence relationships for both single and product moments for the order and upper record statistics are proved. For additional goals, certain joint distributions are also given.

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.

scholarly journals Expectation Properties of Generalized Order Statistics from Poisson Lomax Distribution

2020 ◽  
Vol 9 (3) ◽  
pp. 735-747
Author(s):  
Haseeb Athar ◽  
Zubdahe Noor ◽  
Saima Zarrin ◽  
Hanadi N.S. Almutairi
Keyword(s):  
Order Statistics ◽  
Recurrence Relations ◽  
Generalized Order Statistics ◽  
Lifetime Data ◽  
Product Moments ◽  
Lomax Distribution ◽  
Single And Product Moments ◽  
Generalized Order

The Poisson Lomax distribution was proposed by [3], as a useful model for analyzing lifetime data. In this paper,we have derived recurrence relations for single and product moments of generalized order statistics for this distribution. Further, characterization of the distribution is carried out. Some deductions and particular cases are also discussed.

scholarly journals Progressively Type-II Right Censored Order Statistics from Hjorth Distribution and Related Inference

2020 ◽  
Vol 8 (2) ◽  
pp. 481-498
Author(s):  
NARINDER PUSHKARNA ◽  
JAGDISH SARAN ◽  
KANIKA VERMA
Keyword(s):  
Order Statistics ◽  
Recurrence Relations ◽  
Type Ii ◽  
Sample Sizes ◽  
Product Moments ◽  
Scale Parameters ◽  
Censored Samples ◽  
Progressive Type ◽  
Right Censored Order Statistics ◽  
Single And Product Moments

In this paper some recurrence relations satisfied by single and product moments of progressive Type-II right censored order statistics from Hjorth distribution have been obtained. Then we use these results to compute the moments for all sample sizes and all censoring schemes (R1,R2,...,Rm),m ≤ n, which allow us to obtain BLUEs of location and scale parameters based on progressive type-II right censored samples.

Estimation of the Parameters of Triangular Distribution by Order Statistics

2003 ◽  
Vol 54 (1-2) ◽  
pp. 45-56 ◽  
Author(s):  
Philip Samuel ◽  
P. Yageen Thomas
Keyword(s):  
Order Statistics ◽  
Triangular Distribution ◽  
Unbiased Estimators ◽  
Product Moments ◽  
Scale Parameters ◽  
U Statistics ◽  
Best Linear Unbiased ◽  
Best Linear Unbiased Estimators ◽  
Moments Of Order Statistics ◽  
Single And Product Moments

In this paper, we derive explicit expressions for the single and product moments of order statistics arising from the standard triangular distribution. Best linear unbiased estimators of the location and scale parameters of a triangular distribution based on order statistics are obtained. The efficiencies of these estimators are also compared with estimators based on U-statistics

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