Titlebook: Applied Nonparametric Statistics in Reliability; M. Luz Gámiz,K. B. Kulasekera,Bo Henry Lindqvist Book 2011 Springer-Verlag London Limited

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Book 2011these methods have already proved highly effective in other applied areas of knowledge such as biostatistics or social sciences, nonparametric analyses in reliability currently form an interesting area of study that has not yet been fully explored...Applied Nonparametric Statistics in Reliability. i

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Models for Minimal Repair alternatively, a population of systems of the same characteristics. No assumption is adopted for the functional form of the rocof except concerning the smoothness, which is understood in terms of some properties of derivability. We are also interested in estimating this function under some restrictions of monotonicity.

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Hazard Regression Analysisnt of view. Although the nonparametric estimation of the hazard function may be tackled in several ways, we consider an estimator obtained as the ratio of nonparametric estimators of the conditional density an the survival function

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1614-7839 ferent conditions.Presents some numerical or simulation meth.Nonparametric statistics has probably become the leading methodology for researchers performing data analysis. It is nevertheless true that, whereas these methods have already proved highly effective in other applied areas of knowledge suc

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Entwicklung der chemischen Krystallographietechniques such as kernel smoothing, local linear method, spline method, etc. for the estimation of failure rate functions in the presence of censoring. This is then followed by an introduction to smoothing parameter (bandwidth) selection. A few examples are presented to illustrate the use of some techniques.