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

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, mach...

Description complète

Enregistré dans:
Détails bibliographiques
Collectivité auteur: SpringerLink (Online service)
Autres auteurs: Pilz, Jürgen (Éditeur intellectuel), Melas, Viatcheslav B. (Éditeur intellectuel), Bathke, Arne (Éditeur intellectuel)
Format: Électronique eBook
Langue:anglais
Publié: Cham : Springer International Publishing : Imprint: Springer, 2023.
Édition:1st ed. 2023.
Collection:Contributions to Statistics,
Sujets:
Accès en ligne:https://doi.org/10.1007/978-3-031-40055-1
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
Description
Résumé: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.
Description matérielle:1 online resource (X, 265 p. 85 illus.). 56 illus. in color.
ISBN:9783031400551
ISSN:2628-8966
DOI:10.1007/978-3-031-40055-1