BigInsight congratulates Simon Boge Brant and the department of Mathematics, who successfully defended his thesis “Selected topics in regression with a binary outcome: Fraud detection, and applications of copulas to logistic regression” for the degree of Philosophiae Doctor on November 8th, 2024.

Main research findings:

The thesis concerns different topics that all are related to logistic regression - models for the log-odds where inference is based on a (Bernoulli) likelihood for the conditional distribution of the outcome given covariates. Three papers make up the thesis. The first of these discusses a fraud detection problem, which we summarise in terms of a loss function, and discuss strategies for finding suitable models that approximately minimise this function. In both the second and third papers we present new models, and algorithms for fitting these. In the first of these we construct a boosting algorithm where the base learners are copula-based regression models (Noh et al., 2013; Chang and Joe, 2019), and in the last paper we present an extension of the linear logistic regression model, which is constructed through an R-vine based extension of a discriminant analysis analogue of the linear logistic regression model.

Adjudication committee:

• Professor Thomas Nagler, Ludwig Maximilian University of Munich 

• Professor Bart Baesens, KU Leuven 

• Professor Geir Storvik, University of Oslo

 Supervisors:

• Associate Professor Ingrid Hobæk Haff, University of Oslo

• Associate Professor Riccardo De Bin, University of Oslo