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Titlebook: Advances in Stochastic Models for Reliablity, Quality and Safety; Waltraud Kahle,Elart Collani,Uwe Jensen Book 1998 Birkhäuser Boston 1998

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Chinese Language Learning Sciencestages:.The second part of this paper is an application of this concept to a problem of lifetime estimation, namely the determination of a lower confidence bound for the expectation of a Weibull distribution based on a left- and right-censored sample.
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The Generalized Discrete Linnik Distributions of their probabilities are investigated. Further, the family of survival distributions of a generalized discrete Linnik distributed original observation subjected to a destructive process is determined.
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Maximum Likelihood Estimation With Different Sequential ,-out-of-, Systemsquential .-out-of-. systems, which are allowed to have different structures. Explicit expressions of the maximum likelihood estimators of both the model parameters and the distribution parameters are derived in specific classes of distributions. Moreover, several useful properties of the estimators are presented.
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Book 1998and more important. Thus, there is a need for highly reliable technical devices and systems, for monitoring and controlling their functioning and for planning maintenance and corrective actions to fulfill given requirements considering eco­ nomic limitations. These tasks reflect the wide field of en
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Chinese Language Learning Sciencesre discrete self-decomposable and include the discrete stable as well as the discrete Mittag—Leffler distributions, are introduced and some properties of their probabilities are investigated. Further, the family of survival distributions of a generalized discrete Linnik distributed original observat
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https://doi.org/10.1007/978-981-15-0271-2i.d. life times under censorship without repair. Special investigations are made for Koziol-Green models. In the second part, a general failure-repair model described by counting processes is considered. Under the Koziol-Green condition some results concerning Bayes estimation and the nuisance param
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