On stochastic inequalities and comparisons of reliability measures for weighted distributions
نویسندگان
چکیده
منابع مشابه
On Moment Inequalities and Stochastic Ordering for Weighted Reliability Measures
We obtain stochastic inequalities, error bounds, and classification probability for a general class of distributions. We introduce the notion of variability ordering via the probability functional and comparisons made for the weighted and the original distributions. We present moment inequalities, comparisons, and applications. 2000 Mathematics Subject Classification. 62N05, 62B10.
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In this note, stochastic comparisons and results for weighted and Lindley models are presented. Approximation of weighted distributions via Lindley distribution in the class of increasing failure rate (IFR) and decreasing failure rate (DFR) weighted distributions with monotone weight functions are obtained including approximations via the length-biased Lindley distribution. Some useful bounds a...
متن کاملcompactifications and function spaces on weighted semigruops
chapter one is devoted to a moderate discussion on preliminaries, according to our requirements. chapter two which is based on our work in (24) is devoted introducting weighted semigroups (s, w), and studying some famous function spaces on them, especially the relations between go (s, w) and other function speces are invesigated. in fact this chapter is a complement to (32). one of the main fea...
15 صفحه اولThe behavior of the reliability functions and stochastic orders in family of the Kumaraswamy-G distributions
The Kumaraswamy distribution is a two-parameter distribution on the interval (0,1) that is very similar to beta distribution. This distribution is applicable to many natural phenomena whose outcomes have lower and upper bounds, such as the proportion of people from society who consume certain products in a given interval. In this paper, we introduce the family of Kumaraswamy-G distribution, an...
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ژورنال
عنوان ژورنال: Mathematical Problems in Engineering
سال: 2002
ISSN: 1024-123X,1563-5147
DOI: 10.1080/10241230211380