Bayesian Estimation of a Monotone Regression Function: A method described by Neelon and Dunson applied to climate data

The goal of this thesis is to implement and experiment with a Bayesian way of estimating a (smooth) monotone regression function by applying it to climate data. The method we use is proposed by Neelon and Dunson. This method uses a piece-wise linear model for the unknown regression function and enforces the monotonicity constraint by the...

Bayesian system identification for structures considering spatial and temporal dependencies

Bayesian system identification, including parameter estimation and model selection, is widely used to infer partially known, unobservable parameters of the models of physical systems when measurement data is available. A common assumption in the Bayesian system identification...

The Observational Method for building pits in soft-soil conditions: A study on measurement-processing and feasibility of the Observational method Ab Initio approach.

In the Observational Method Ab Initio approach a flexible design and construction plan is established to allow anticipation to observational feedback during the construction phase. This way, the structural design can be optimized to the in-situ conditions which is beneficial from both safety and economic point of view. In the application of...