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

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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.

Author(s): Jürgen Pilz; Viatcheslav B. Melas; Arne Bathke
Series: Contributions to Statistics
Edition: 1
Publisher: Springer Nature Switzerland
Year: 2023

Language: English
Pages: x; 265
City: Cham
Tags: Statistical Theory and Methods; Statistics and Computing/Statistics Programs; Machine Learning; Applied Statistics; Statistical Theory and Methods