Top Posts Tagged with #weibull distribution

Bayesian Approach to Reliability Estimation | Chapter 09 | Advances in Mathematics and Computer Science Vol. 4

In this chapter Bayes estimators of the reliability function R(t) under Type II censoring of Weibull distribution have been obtained by taking non-informative and beta prior distributions. The loss functions used are squared error, linex, precautionary and entropy.

Author(s) Details

Dr. Arun Kumar Rao Department of Mathematics & Statistics, DDU Gorakhpur University, Gorakhpur, India.

Dr. Himanshu Pandey Department of Mathematics & Statistics, DDU Gorakhpur University, Gorakhpur, India.

View Volume: http://bp.bookpi.org/index.php/bpi/catalog/book/97

#Books #Science #Reliability #Weibull distribution #non-informative and beta prior #squared error #linex #precautionary and entropy loss functions

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New Discovery May Improve Prediction Of Volcano Eruptions

https://earthchangesmedia.com/new-discovery-may-improve-prediction-of-volcano-eruptions

Volcanoes are among the most dangerous and least predictable natural forces on our planet. New findings may contribute to better volcano surveillance and eruption prognoses. To understand the processes at work inside volcanoes, geologists survey cracks filled with magma, so-called dykes. These…

Volcanoes are…

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#Uppsala University #Weibull distribution

Read the full paper at: http://www.scirp.org/journal/PaperInformation.aspx?PaperID=49744 DOI: 10.4236/ojs.2014.48053 Author(s) Al Omari Mohammed Ahmed Affiliation(s) Department of Mathematics, Faculty of Arts and Science in Qilwah, Al Baha University, Baha, KSA. ABSTRACT This study considers the estimation of Maximum Likelihood Estimator and the Bayesian Estimator of the Weibull distribution with interval-censored data. The Bayesian estimation can’t be used to solve the parameters analytically thus Markov Chain Monte Carlo is used, where the full conditional distribution for the scale and shape parameters are obtained via Metropolis-Hastings algorithm. Also Lindley’s approximation is used. The two methods are compared to maximum likelihood counterparts and the comparisons are made with respect to the mean square error (MSE) to determine the best for estimating of the scale and shape parameters. eww140919gjr KEYWORDS Weibull Distribution, Bayesian Method, Interval Censored, Metropolis-Hastings Algorithm, Lindley’s Approximation

#Weibull Distribution #Bayesian Method #Interval Censored #Metropolis-Hastings Algorithm #Lindley’s Approximation

New Discovery May Improve Prediction Of Volcano Eruptions

http://earthchangesmedia.com/new-discovery-may-improve-prediction-of-volcano-eruptions