The Beta Generalized Weibull distribution: Properties and applications
The Beta Generalized Weibull distribution: Properties and applications
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DOI：
10.1016/j.ress.2012.02.003
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发表时间：
2012-06
期刊：
影响因子：
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通讯作者：
Neetu Singla;Kanchan Jain;Suresh Sharma
中科院分区：
文献类型：
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作者：
Neetu Singla;Kanchan Jain;Suresh Sharma
引入了一种称为Beta广义威布尔（BGW）分布的五参数分布。Beta广义指数（BGE）、Beta威布尔（BW）、广义或指数威布尔（GW或EW）、广义瑞利（GR）、Beta指数（BE）、广义指数（GE）、威布尔、瑞利和指数是它的子模型。累积分布函数（cdf）和概率密度函数（pdf）已表示为广义威布尔cdf和pdf的混合。导出了k阶矩。给出了导出极大似然估计量和观测信息矩阵元素的非线性方程。该分布被发现是上级现有的子模型被拟合到两个真实的数据集。
A five-parameter distribution called Beta Generalized Weibull (BGW) distribution is introduced. Beta Generalized Exponential (BGE), Beta Weibull (BW), Generalized or Exponentiated Weibull (GW or EW), Generalized Rayleigh (GR), Beta Exponential (BE), Generalized Exponential (GE), Weibull, Rayleigh and Exponential are its sub models. The cumulative distribution function (cdf) and the probability density function (pdf) have been expressed as mixtures of the Generalized Weibull cdfs and pdfs. The kth order moment has been derived. The non-linear equations for deriving the maximum likelihood estimators and the elements of the observed information matrix are presented. The distribution is found to be superior to the existing sub models on being fitted to two real data sets.