نتایج جستجو برای: weibull distribution

تعداد نتایج: 610714  

2003

Two approaches are used to assess the distribution assumptions. One is by implementing numerically convoluted, theoretical Goodness of Fit (GoF) tests such as the Chi Square, Anderson Darling or Kolmogorov-Smirnov. Their lengthy calculations often require the use of specialized software, not always readily available. On the other hand, there exist practical procedures that are easy to understan...

Journal: :Journal of Statistical Theory and Applications 2019

Journal: :Journal of Statistical Distributions and Applications 2016

Journal: :Hacettepe Journal of Mathematics and Statistics 2014

Journal: :Journal of the National Science Foundation of Sri Lanka 2019

Journal: :Pakistan Journal of Statistics and Operation Research 2014

Journal: :international journal of industrial engineering and productional research- 0
fernando antonio moala [email protected]

the weibull distribution has been widely used in survival and engineering reliability analysis. in life testing experiments is fairly common practice to terminate the experiment before all the items have failed, that means the data are censored. thus, the main objective of this paper is to estimate the reliability function of the weibull distribution with uncensored and censored data by using b...

2012
Francis Pascual

This article proposes methods for monitoring Weibull processes when data collection is restricted to one observation per sampling period. Because the Weibull distribution is an asymmetric distribution, it is not appropriate to apply normal-based individuals-movingrange charts to Weibull data. A transformation of Weibull to approximate normality prior to applying normal-based methods has been su...

2015
A. El-gohary A. H. El-bassiouny M. El-morshedy

In this paper, a new two parameters model is introduced. We called it the inverse flexible Weibull extension (IFW) distribution. Several properties of this distribution have been discussed. The maximum likelihood estimators of the parameters are derived. Two real data sets are analyzed using the new model, which show that the new model fits the data better than some other very well known models.

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