Moments of Generalized Upper Record Values from Weibull- Power Function Distribution and Characterization

2020 ◽  
Vol 9 (2) ◽  
pp. 309-318
Keyword(s):  
Power Function ◽  
Record Values ◽  
Function Distribution ◽  
Upper Record Values ◽  
Power Function Distribution ◽  
Upper Record

scholarly journals A Characterization and Recurrence Relations of Moments of the Size-Biased Power Function Distribution by Lower Record Values

2018 ◽  
Vol 7 (5) ◽  
pp. 1
Author(s):  
Shakila Bashir ◽  
Mujahid Rasul
Keyword(s):  
Power Function ◽  
Recurrence Relations ◽  
Survival Function ◽  
Joint Probability ◽  
Record Values ◽  
Cumulative Distribution ◽  
Function Distribution ◽  
Power Function Distribution ◽  
Lower Record ◽  
Lower Record Values

A variety of research papers have been published on record values from various continuous distributions. This paper investigated lower record values from the size-biased power function distribution (LR-SPFD). Some basic properties including moments, skewness, kurtosis, Shannon entropy, cumulative distribution function, survival function and hazard function of the lower record values from SPFD have been discussed. The joint probability density function (pdf) of $n^{th}$ and $m^{th}$ lower record values from SPFD is developed. Recurrence relations of the single and product moments of the LR-SPFD have been derived. A characterization of the lower record values from SPFD is also developed.

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 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 Evaluating the Lifetime Performance Index Based on the Bayesian Estimation for the Rayleigh Lifetime Products with the Upper Record Values

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Wen-Chuan Lee ◽  
Jong-Wuu Wu ◽  
Ching-Wen Hong ◽  
Shie-Fan Hong
Keyword(s):  
Loss Function ◽  
Performance Index ◽  
Resource Planning ◽  
Record Values ◽  
Testing Procedure ◽  
Assessment System ◽  
Squared Error Loss Function ◽  
Lifetime Performance ◽  
Upper Record Values ◽  
Upper Record

Quality management is very important for many manufacturing industries. Process capability analysis has been widely applied in the field of quality control to monitor the performance of industrial processes. Hence, the lifetime performance indexCLis utilized to measure the performance of product, whereLis the lower specification limit. This study constructs a Bayesian estimator ofCLunder a Rayleigh distribution with the upper record values. The Bayesian estimations are based on squared-error loss function, linear exponential loss function, and general entropy loss function, respectively. Further, the Bayesian estimators ofCLare utilized to construct the testing procedure forCLbased on a credible interval in the condition of knownL. The proposed testing procedure not only can handle nonnormal lifetime data, but also can handle the upper record values. Moreover, the managers can employ the testing procedure to determine whether the lifetime performance of the Rayleigh products adheres to the required level. The hypothesis testing procedure is a quality performance assessment system in enterprise resource planning (ERP).

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