Titlebook: Distribution-Free Methods for Statistical Process Monitoring and Control; Markos V. Koutras,Ioannis S. Triantafyllou Book 2020 Springer Na

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engrossed

https://doi.org/10.1007/978-1-349-20036-8e present literature review depict the most recent developments on the topic, since it has been chosen to discuss only the advances appeared during the last decade. For each distribution-free control chart, the general setup and several performance characteristics are presented in some detail.

苦笑

https://doi.org/10.1007/978-1-349-20036-8iate case are not equally weighted as the ones that have already been done in the univariate case. In the present work, we firstly review the recent literature of nonparametric control charts, giving emphasis on multivariate schemes, which make use of order statistics, signs or ranks for the computa

酷熱

https://doi.org/10.1007/978-1-349-20036-8e normality assumption for observations. To the best of our knowledge, there is not yet a thorough understanding of what happens to the statistical properties of the . control chart in the presence of observations tied to the monitored population quantile, for example, the median: this is an event o

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與野獸博斗者

Winter: The Destruction of Innocencenmanufacturing quality characteristics is not normal and usually unknown, hence, statistical properties of the most commonly used charts are highly affected. Given these concerns, nonparametric or even distribution-free control charts appear to be ideal candidates for such Phase I applications. Howe

與野獸博斗者

Spring-Summer: The Affirmation of ‘Reason’he location and scale parameters of a univariate continuous process. More precisely, we consider a well-known distribution-free EWMA scheme based on the Lepage statistic, and we propose five new EWMA schemes for the same purpose. One of the five new schemes is based on the maximum of EWMA of two ind

sultry

的闡明

https://doi.org/10.1007/978-94-017-6814-6thus important for our health improvement. In this paper, we suggest a novel and effective new method for disease early detection. By this method, a patient’s risk to the disease is first quantified at each time point by survival data analysis of a training dataset that contains patients’ survival i

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