Bayesian Point Prediction for Rayleigh distribution when observations are censored to left and right
In this paper we utilize Bayesian approach to obtain predictors of the future observation from Rayleigh distribution when observations are censored to left as well as to the right. Bayesian predictor is obtained using natural conjugate prior under asymmetric loss function. Bayesian predictor is also obtained under the squared error loss function. For each loss predictive risks are calculated. Lastly, predictors are compared for the smallest future ordered observation on the basis of 1000 randomly generated sample using Monte Carlo simulation technique.
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V. Shastri; D. S. Pal, "Bayesian Point Prediction for Rayleigh distribution when observations are censored to left and right", Journal of Ultra Scientist of Physical Sciences, Volume 30, Issue 2, Page Number 97-109, 2018Copy the following to cite this URL:
V. Shastri; D. S. Pal, "Bayesian Point Prediction for Rayleigh distribution when observations are censored to left and right", Journal of Ultra Scientist of Physical Sciences, Volume 30, Issue 2, Page Number 97-109, 2018Available from: https://www.ultrascientist.org/paper/1151/bayesian-point-prediction-for-rayleigh-distribution-when-observations-are-censored-to-left-and-right
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