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Titlebook: Statistical Modeling and Simulation for Experimental Design and Machine Learning Applications; Selected Contributio Jürgen Pilz,Viatcheslav

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書目名稱Statistical Modeling and Simulation for Experimental Design and Machine Learning Applications
副標(biāo)題Selected Contributio
編輯Jürgen Pilz,Viatcheslav B. Melas,Arne Bathke
視頻videohttp://file.papertrans.cn/877/876560/876560.mp4
概述Presents current developments in statistical modeling and simulation.Focuses on experimental design and machine learning applications.Features invited contributions
叢書名稱Contributions to Statistics
圖書封面Titlebook: Statistical Modeling and Simulation for Experimental Design and Machine Learning Applications; Selected Contributio Jürgen Pilz,Viatcheslav
描述This volume presents a selection of articles on statistical modeling and simulation, with a focus on different aspects of statistical estimation and testing problems, the design of experiments, reliability and queueing theory, inventory analysis, and the interplay between statistical inference, machine learning methods and related applications. The refereed contributions originate from the 10th International Workshop on Simulation and Statistics, SimStat 2019, which was held in Salzburg, Austria, September 2–6, 2019, and were either presented at the conference or developed afterwards, relating closely to the topics of the workshop. The book is intended for statisticians and Ph.D. students who seek current developments and applications in the field.
出版日期Conference proceedings 2023
關(guān)鍵詞Statistical Modeling; Stochastic Simulation; Design of Experiments; Machine Learning; Statistical Comput
版次1
doihttps://doi.org/10.1007/978-3-031-40055-1
isbn_softcover978-3-031-40057-5
isbn_ebook978-3-031-40055-1Series ISSN 1431-1968 Series E-ISSN 2628-8966
issn_series 1431-1968
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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that that best possible care is realized at the bedside. All of the evidence suggests that PET is central to such optimal cancer care. In addition to the distinguished cast of physicians and researchers who con978-1-4939-3837-7978-0-387-34641-0
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N. P. Alexeyeva,F. S. Al-juboori,E. P. Skuratthat that best possible care is realized at the bedside. All of the evidence suggests that PET is central to such optimal cancer care. In addition to the distinguished cast of physicians and researchers who con978-1-4939-3837-7978-0-387-34641-0
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Likelihood Ratios in Forensics: What They Are and What They Are Notce database. These parameters are the within-subject variance, the between-subject variance, and the population mean for the univariate evidence measurements. Using the glass fragment example in [.] and [.], the relationship between Lindley’s likelihood ratio and these parameters is illustrated with
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