Estimation of Location and Scale Parameters by Order Statistics from Singly and Doubly Censored Samples, Part I. The Normal Distribution up to Samples of Size 10

1958 ◽  
Vol 12 (64) ◽  
pp. 289
Author(s):  
A. C. Cohen ◽  
A. E. Sarhan ◽  
B. G. Greenberg
Keyword(s):  
Normal Distribution ◽  
Order Statistics ◽  
Scale Parameters ◽  
Censored Samples ◽  
Doubly Censored

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.

Stochastic comparison of parallel systems with Pareto components

2021 ◽  
pp. 1-13
Author(s):  
Sameen Naqvi ◽  
Weiyong Ding ◽  
Peng Zhao
Keyword(s):  
Order Statistics ◽  
Extreme Value Theory ◽  
Pareto Distribution ◽  
Parallel Systems ◽  
Value Theory ◽  
Extreme Value ◽  
Stochastic Comparison ◽  
Shape Parameters ◽  
Scale Parameters ◽  
Dispersive Ordering

Abstract Pareto distribution is an important distribution in extreme value theory. In this paper, we consider parallel systems with Pareto components and study the effect of heterogeneity on skewness of such systems. It is shown that, when the lifetimes of components have different shape parameters, the parallel system with heterogeneous Pareto component lifetimes is more skewed than the system with independent and identically distributed Pareto components. However, for the case when the lifetimes of components have different scale parameters, the result gets reversed in the sense of star ordering. We also establish the relation between star ordering and dispersive ordering by extending the result of Deshpande and Kochar [(1983). Dispersive ordering is the same as tail ordering. Advances in Applied Probability 15(3): 686–687] from support $(0, \infty )$ to general supports $(a, \infty )$ , $a > 0$ . As a consequence, we obtain some new results on dispersion of order statistics from heterogeneous Pareto samples with respect to dispersive ordering.

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