scholarly journals Two sample Bayesian prediction intervals for order statistics based on the inverse exponential-type distributions using right censored sample

2011 ◽  
Vol 19 (3) ◽  
pp. 102-105 ◽  
Author(s):  
M.M. Mohie El-Din ◽  
Y. Abdel-Aty ◽  
A.R. Shafay
Keyword(s):  
Order Statistics ◽  
Exponential Type ◽  
Bayesian Prediction ◽  
Prediction Intervals ◽  
Censored Sample

Bayesian Prediction Bounds for the Exponential-Type Distribution Based on Ordered Ranked Set Sampling

2016 ◽  
Vol 31 (1) ◽  
Author(s):  
Mohammed S. Kotb
Keyword(s):  
Exponential Type ◽  
Bayesian Prediction ◽  
Prediction Intervals ◽  
Prior Density ◽  
Type Distribution ◽  
Ranked Set Sample ◽  
Cumulative Function ◽  
Sample Method ◽  
Special Case ◽  
Sample Case

AbstractWe suggest a ranked set sample method to improve Bayesian prediction intervals. The paper deals with the Bayesian prediction intervals in the context of an ordered ranked set sample from a certain class of exponential-type distributions. A proper general prior density function is used and the predictive cumulative function is obtained in the two-sample case. The special case of linear exponential distributed observations is considered and completed with numerical results.

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>

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