Predicting future order statistics with random sample size

Faculty Science Year: 2021
Type of Publication: ZU Hosted Pages:
Authors:
Journal: Mathematics AIMS Volume:
Keywords : Predicting future order statistics with random    
Abstract:
We suggest a new method for constructing an ecient point predictor for the future order statistics when the sample size is a random variable. The suggested point predictor is based on some characterization properties of the distributions of order statistics. For several distributions, including the mixture distribution, the performance of the suggested predictor is evaluated by means of a comprehensive simulation study. Three examples of real lifetime data-sets are analyzed by using this method and compared with an ecient recent method given by Barakat et al. [1], that deals with non-random sample sizes. One of these examples predicts the accumulative new cases per million for infection of the new Coronavirus (COVID-19).
   
     
 
       

Author Related Publications

  • Haroun Mohammed Abdel-Fattah Barakat, "Random translation, dilation and contraction of order statistics", El-Sevier, 2014 More
  • Haroun Mohammed Abdel-Fattah Barakat, "Limit theory for bivariate extreme generalized order statistics and dual generalized order statistics", ALEA publisher, 2014 More
  • Haroun Mohammed Abdel-Fattah Barakat, "Asymptotic distributions of order statistics and record values arising from the class of beta-generated distributions", Taylor &Francis, 2014 More
  • Haroun Mohammed Abdel-Fattah Barakat, "LIMIT THEORY FOR JOINT GENERALIZED ORDER STATISTICS", Taylor &Francis, 2014 More
  • Haroun Mohammed Abdel-Fattah Barakat, "Statistical Modeling of Extreme Values with Applications to Air Pollution", Science Puplications publisher, 2012 More

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