Unsupervised classification of ships and their operations

In this modern age, data is being generated constantly and data is being saved for analysis everywhere. In the maritime industry, interest in the analysis of ship data has grown over the years. In this thesis, we will take a look at AIS data coupled with sea state data. AIS data is data generated from the ship, concerning the ship locations,...

Bootstrapping in the Cox-model with interval censored observations

In this study the interval censoring case 2 model combined with the Cox model is considered. The event-time distribution function is modeled nonparametrically. Two algorithms are proposed to estimate the event-time distribution function together with the Cox coefficients. Kernel smoothing is applied to the non-parametric MLE of the event-time...

Statistische detectie van trends in klimaatreeksen: Wordt het steeds warmer?

Momenteel zorgen de gigantische bosbranden in Siberië voor onrust en tegelijkertijd voor een bevestiging voor klimaatactivisten. Nergens in de wereld stijgt de temperatuur zo snel als in dit arctisch gebied. Daarnaast probeert voormalig vice-president van Amerika en huidig klimaatactivist Al Gore al jaren men de ernst van temperatuurstijging in...

Latent Dirichlet Allocation: Explained and improved upon for applications in marketing intelligence

In today's digital world, customers give their opinions on a product that they have purchased online in the form of reviews. The industry is interested in these reviews, and wants to know about which topics their clients write, such that the producers can improve products on specific aspects. Topic models can extract the main topics from large...

Statistical modelling of forensic evidence

The evaluation of evidence found at a crime scene is primarily conducted through comparison of two competing statistical hypotheses. In forensic science, there is currently no consensus on the formulation of the competing hypotheses. A main point of discussion is the difference between common source and specific source problems. In a common...

Credit scoring for small medium enterprises using transaction data

Managing credit risk is a vital part of financial institutions. While the research into credit risk models is extensive, transaction data is a relatively untapped data source in these models. We investigate the explanatory value of transaction data for the Bank by developing default classification models for their small medium enterprises (SME)...

Causal inference: An introduction

Experiments have always been the way to study what the effect is of interventions. Causal inference is an important aspect. In this thesis we gave an introduction to causal inference. We did this by giving an example that illustrates the Fundamental Problem of Causal Inference.<br/>The Fundamental Problem of Causal Inference states that it is...

Modeling performance of elite cyclists: The effect of training on performance

Both coaches and cyclists nowadays determine the training schedules for important races based on experience<br/>and gut-feeling. Data are available for the evaluation of training schedules, but a sound scientific<br/>method of accomplishing this does not yet exist. The biggest hurdle in developing such a method for cycling<br/>is the absence of...

Variable selection and shrinkage in the Cox proportional hazards model

In this thesis, shrinkage and variable selection is used on one of the most famous models in survival analysis, the Cox proportional hazards model. <br/>First, the Cox proportional hazards model is statistically observed, by deriving the so called partial likelihood. This likelihood type of function is used for maximum likelihood estimation of...