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

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Weitere Verfasser: Pilz, Jürgen (HerausgeberIn), Melas, Viatcheslav B. (HerausgeberIn), Bathke, Arne (HerausgeberIn)
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Sprache:English
Veröffentlicht: Cham Springer International Publishing 2023
Cham Springer
Ausgabe:1st ed. 2023
Schriftenreihe:Contributions to Statistics
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series2 Contributions to Statistics
spellingShingle Statistical Modeling and Simulation for Experimental Design and Machine Learning Applications Selected Contributions from SimStat 2019 and Invited Papers
Statistical Theory and Methods
Statistics and Computing
Design of Experiments
Machine Learning
Applied Statistics
Stochastic Modelling in Statistics
Statistics 
Mathematical statistics / Data processing
Experimental design
Machine learning
Stochastic models
title Statistical Modeling and Simulation for Experimental Design and Machine Learning Applications Selected Contributions from SimStat 2019 and Invited Papers
title_auth Statistical Modeling and Simulation for Experimental Design and Machine Learning Applications Selected Contributions from SimStat 2019 and Invited Papers
title_exact_search Statistical Modeling and Simulation for Experimental Design and Machine Learning Applications Selected Contributions from SimStat 2019 and Invited Papers
title_exact_search_txtP Statistical Modeling and Simulation for Experimental Design and Machine Learning Applications Selected Contributions from SimStat 2019 and Invited Papers
title_full Statistical Modeling and Simulation for Experimental Design and Machine Learning Applications Selected Contributions from SimStat 2019 and Invited Papers edited by Jürgen Pilz, Viatcheslav B. Melas, Arne Bathke
title_fullStr Statistical Modeling and Simulation for Experimental Design and Machine Learning Applications Selected Contributions from SimStat 2019 and Invited Papers edited by Jürgen Pilz, Viatcheslav B. Melas, Arne Bathke
title_full_unstemmed Statistical Modeling and Simulation for Experimental Design and Machine Learning Applications Selected Contributions from SimStat 2019 and Invited Papers edited by Jürgen Pilz, Viatcheslav B. Melas, Arne Bathke
title_short Statistical Modeling and Simulation for Experimental Design and Machine Learning Applications
title_sort statistical modeling and simulation for experimental design and machine learning applications selected contributions from simstat 2019 and invited papers
title_sub Selected Contributions from SimStat 2019 and Invited Papers
topic Statistical Theory and Methods
Statistics and Computing
Design of Experiments
Machine Learning
Applied Statistics
Stochastic Modelling in Statistics
Statistics 
Mathematical statistics / Data processing
Experimental design
Machine learning
Stochastic models
topic_facet Statistical Theory and Methods
Statistics and Computing
Design of Experiments
Machine Learning
Applied Statistics
Stochastic Modelling in Statistics
Statistics 
Mathematical statistics / Data processing
Experimental design
Machine learning
Stochastic models
url https://doi.org/10.1007/978-3-031-40055-1
work_keys_str_mv AT pilzjurgen statisticalmodelingandsimulationforexperimentaldesignandmachinelearningapplicationsselectedcontributionsfromsimstat2019andinvitedpapers
AT melasviatcheslavb statisticalmodelingandsimulationforexperimentaldesignandmachinelearningapplicationsselectedcontributionsfromsimstat2019andinvitedpapers
AT bathkearne statisticalmodelingandsimulationforexperimentaldesignandmachinelearningapplicationsselectedcontributionsfromsimstat2019andinvitedpapers