Climate change induced uncertainties in future coastal ecosystem state

This thesis presents a doctoral research where statistical concepts and techniques are applied to problems at the interface of marine and atmospheric processes. The research was conducted at the Statistics group of the Delft Institute of Applied Mathematics (TU Delft) and the Marine and Coastal unit of Deltares. The main objective of the work is...

Approximations and transformations of piecewise deterministic Monte Carlo algorithms

This thesis studies methods to improve the applicability and the performance of Markov Chain Monte Carlo (MCMC) algorithms based on Piecewise Deterministic Markov processes (PDMPs). First, we discuss the key ideas that lay the foundations of the field of MCMC, spanning from the Metropolis-Hastings algorithm to PDMC methods, emphasising a common...

Statistical post processing of extreme weather forecasts

In this thesis we develop several statistical methods to estimate high conditional quantiles to use for statistical post-processing of weather forecasts. We propose methodologies that combine theory from extreme value statistics and machine learning algorithms in order to estimate high conditional quantiles in large covariate spaces. In...

A data-driven and machine-learning study on microstructure-property relations in steel

Multi-phase metallic materials such as Advanced High-Strength Steels (AHSS) are of great importance in a wide variety of high-tech industries due to their higher strength compared to conventional (mild) forming steels. The higher strength leads to various advantages in weight, safety and environmental friendliness. In order to develop new AHHS...

Bayesian Nonparametric Estimation with Shape Constraints

This thesis deals with a number of statistical problems where either censoring<br/>or shape-constraints play a role. These problems have mostly been treated from a frequentist statistical perspective. Over the past decades, the Bayesian approach<br/>to statistics has gained popularity and this is the approach that is adopted in this<br/>thesis....

Statistical analysis of the relation between metallic microstructures and mechanical properties

This thesis aims at the development of physical relations between the intricate 3D features of metallic microstructures and the mechanical properties of the material. For understanding which are the microstructural determinants of the resultingmechanical behaviour of metals, a deep quantitative characterisation of the microstructure is needed....

Smooth nonparametric estimation under monotonicity constraints

In this thesis we address the problem of estimating a curve of interest (which might be a probability density, a failure rate or a regression function) under monotonicity constraints. The main concern is investigating large sample distributional properties of smooth isotonic estimators, which have a faster rate of convergence and a nicer...

Bayesian inference for discretely observed diffusion processes

In dit proefschrift bestuderen we diffusie processen, it zijn Markovprocessen met continue paden in een euclidische ruimte die bepaalde stochastische differentiaalvergelijkingen oplossen. Wij ontwikkelen en implementeren Bayesiaanse procedures voor de schatting van de drift en diffusie coefficienten wanneer slechts discrete observaties van het...

Stereological Estimation of Anisotropic Microstructural Features: Applying an Oriented Cylinder Model to Dual Phase Steel

Microstructural banding is explored in 2D and 3D using serial sectioned micrographs. The banding is quantified using two parameters called the Band Continuity Index Cb and the Perpendicular Continuity Index Cp. The indexes determined from the 2D micrographs is shown to be sufficient for estimating the distribution of the bands in 3D. A...

Shape Constrained Nonparametric Estimation in the Cox Model

The events of interest in any survival analysis study are regularly subject to censoring. There are various censoring schemes, including right or left censoring, and interval censoring. The most frequent censoring scheme is the right censoring, where subjects might drop out of the study or simply because not all events of interest occur before...

Current Status Censoring Models: Smooth estimators and their asymptotic properties

Statistics deals with answering questions based on collected data. In medical applications, the quantity of interest can often not be observed directly. They are censored. It is a challenge to answer the question as precisely as possible based on the incomplete data. The quantity of interest can be censored in many different ways. In HIV vaccine...