Frequentistische en Bayesiaanse statistiek in de forensische statistiek

In de statistiek zijn er verschillende methodes voor het uitvoeren van model selectie. Het verschil in deze methodes komt voort uit het verschil in stromingen. Voor niet-geneste model selectie zijn de meest ganbare stromingen de Bayes Factor en de likelihood ratio. D. M. Ommen en C. P. Saunders presenteerden theoretische resultaten voor de...

The AIC-BIC dilemma: An in-depth look

In research there is often a need to choose between multiple competing models. Two popular criteria for model selection are the AIC and BIC. The AIC excels in estimating the best model for the unknown data generating process. The BIC on the other hand is consistent in finding the true model. It is clear that for model selection these two...

Categorical based feature modeling on a zero inflated performance measure

ASML produces TwinScan NXT machines that are used for the production of microchips. The machines ensure that an accurate pattern of DUV-light passes a lens and that it is projected as accurate as possible on the wafer. To ensure that the focal point of the converged DUV-light falls exactly onto the wafer, the leveling functionality is of great...

A time-reversed model identification approach to time series forecasting

In this thesis, I introduce a novel model identification approach to time series forecasting. For linear stationary processes, such as AR processes, the direction of time is independent of the model parameters. By combining theoretical principles of time-reversibility in time series with conventional modeling approaches such as information...

Long-term Effect of MPH on White Matter Tracts of Adults with ADHD: An Application of Consistent Model Selection followed by TBSS

We focused on analysis of long-term medication influenced white matter tracts based on diffusion-weighted MRI brain images of patients with ADHD disorder. We applied a framework of consistent model selection with Tract-based spatial statistics (TBSS) to give proper and consistent modelling of fiber-crossing in white matter. An orientation atlas...

Restoration of Missing Data using a Human Adaptive Framework: The Cleansing Algorithm

Improving data quality is of the utmost importance for any data-driven company, as data quality is unmistakably tied to business analytics and processes. One method to improve upon data quality is to restore missing and wrong data entries.  </p><p class="MsoNormal">The goal of this research is construct an algorithm such...