Cuvillier Verlag

35 Jahre Kompetenz im wissenschaftlichen Publizieren
Internationaler Fachverlag für Wissenschaft und Wirtschaft

Cuvillier Verlag

De En Es
Two-dimensional Regression Modelling with Copula Dependencies and a Focus on Count Data and Sports Applications

Printausgabe
EUR 43,40

E-Book
EUR 30,40

Two-dimensional Regression Modelling with Copula Dependencies and a Focus on Count Data and Sports Applications

Hendrik van der Wurp (Autor)

Vorschau

Leseprobe, PDF (380 KB)
Inhaltsverzeichnis, PDF (93 KB)

This work was fundamentally motivated by the application of regression modelling to football match outcomes and specifically FIFA World Cups. Modelling football results is a rather popular topic. However, there is no gold standard on how to tackle the bivariate nature of match outcomes and how to assess the possible underlying dependency thereof. This work proposes to use the mathematical structure of copulas to include the bivariate dependency structure within the modelling process. In this context, two regularization approaches were implemented into existing infrastructure and multiple showcases of the methodology are presented.

ISBN-13 (Printausgabe) 9783736979253
ISBN-13 (E-Book) 9783736969254
Sprache Englisch
Seitenanzahl 116
Umschlagkaschierung glänzend
Auflage 1.
Erscheinungsort Göttingen
Promotionsort Dortmund
Erscheinungsdatum 12.12.2023
Allgemeine Einordnung Dissertation
Fachbereiche Statistik und Operations Research, Wirtschaftsmathematik
Schlagwörter Statistics, Statistical Modelling, Regression, LASSO, Regression Modelling, Copula, Football, Association Football, Dependencies, Football Results, Competitive Settings, Machine Learning, Regularisation, Feature Selection, FIFA World Cups, Joint Modelling, Count Data, Sports Applications, Betting, Bundesliga, Soccer, Primera Division, Data Analysis, Bivariate Response, Cross Validation, Benchmarking, Model Validation, Forecasting, Correlation, Approximation, Statistik, Statistische Modellierung, Regression, Fußball, Abhängigkeiten, Variablenauswahl, FIFA Weltmeisterschaften, Pönalisierung, Fußballergebnisse, Kompetitive Szenarien, Maschinelles Lernen, Zähldaten, Sportanwendungen, Wetten