| Dewey Class |
519.5 |
| Titel |
Statistical Modeling and Simulation for Experimental Design and Machine Learning Applications (EBook :) : Selected Contributions from SimStat 2019 and Invited Papers / / edited by Jürgen Pilz, Viatcheslav B. Melas, Arne Bathke. |
| Added Personal Name |
Pilz, Jürgen |
| Melas, Viatcheslav B. |
| Bathke, Arne |
| Other name(s) |
SpringerLink (Online service) |
| Edition statement |
1st ed. 2023. |
| Veröffentl |
Cham : : Springer International Publishing : : Imprint: Springer, , 2023. |
| Physical Details |
X, 265 p. 85 illus., 56 illus. in color. : online resource. |
| Reihe |
Contributions to Statistics 2628-8966 |
| ISBN |
9783031400551 |
| Summary Note |
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.: |
| Mode of acces to digital resource |
Digital reproduction.- |
| Cham : |
| Springer International Publishing, |
| 2023. - |
| Mode of access: World Wide Web. System requirements: Internet Explorer 6.0 (or higher) or Firefox 2.0 (or higher). Available as searchable text in PDF format. |
| System details note |
Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users). |
| Internet Site |
https://doi.org/10.1007/978-3-031-40055-1 |
| LINKS ZU 'VERWANDTEN WERKEN |
Schlagwörter: .
Applied Statistics .
Design of Experiments .
Experimental design .
Machine Learning .
Mathematical Statistics .
Statistical Theory and Methods .
Statistics .
Statistics and Computing .
Stochastic Modelling in Statistics .
Stochastic models .
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