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Statistical Modeling and Simulation for Experimental Design and Machine Learning Applications Selected Contributions from SimStat 2019 and Invited Papers

Title
Statistical Modeling and Simulation for Experimental Design and Machine Learning Applications [electronic resource] : Selected Contributions from SimStat 2019 and Invited Papers / edited by Jürgen Pilz, Viatcheslav B. Melas, Arne Bathke.
ISBN
9783031400551
Edition
1st ed. 2023.
Publication
Cham : Springer International Publishing : Imprint: Springer, 2023.
Physical Description
1 online resource (X, 265 p.) 85 illus., 56 illus. in color.
Local Notes
Access is available to the Yale community.
Access and use
Access restricted by licensing agreement.
Summary
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.
Variant and related titles
Springer ENIN.
Other formats
Printed edition:
Printed edition:
Printed edition:
Format
Books / Online
Language
English
Added to Catalog
November 02, 2023
Series
Contributions to Statistics
Contributions to Statistics
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