Companies strive to improve their business processes in order to remain competitive. Process mining aims to infer meaningful insights from process-related data and attracted the attention of practitioners, tool-vendors, and researchers in recent years. Traditionally, event logs are assumed to describe the as-is situation. But this is not necessarily the case in environments where logging may be...

This paper deals with the design problem for recovering a response surface by using a nonparametric Bayesian approach. The criterion for selecting the designs is based on the asymptotic average estimation variance, and three priors for the response are specified. We found the optimal design that minimizes the criterion over the lattice designs with s q-level factors and N runs. The approach we ...

Abstract: Robust design (RD), implemented in statistical and mathematical procedures to simultaneously minimise the process bias and variability, is widely used in many areas of engineering and technology to represent complex real-world industrial settings. For RD modelling and optimisation, response surface methodology (RSM) is often utilised as an estimation method to represent the functional...

Classification rates on out-of-sample predictions can often be improved through the use of model selection when fitting a model on the training data. Using correlated predictors or fitting a model of too high a dimension can lead to overfitting, which in turn leads to poor out-of-sample performance. I will discuss methodology using the Bayesian Information Criterion (BIC) of Schwarz (1978) that...