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1. Gaussian Bridges : Modeling and Inference
Sammanfattning : This thesis consists of a summary and five papers, dealing with the modeling of Gaussian bridges and membranes and inference for the α-Brownian bridge.In Paper I we study continuous Gaussian processes conditioned that certain functionals of their sample paths vanish. We deduce anticipative and non-anticipative representations for them. LÄS MER
2. Bayesian Inference for Nonlinear Dynamical Systems : Applications and Software Implementation
Sammanfattning : The topic of this thesis is estimation of nonlinear dynamical systems, focusing on the use of methods such as particle filtering and smoothing. There are three areas of contributions: software implementation, applications of nonlinear estimation and some theoretical extensions to existing algorithms. LÄS MER
3. Selection of smoothing parameters with application in causal inference
Sammanfattning : This thesis is a contribution to the research area concerned with selection of smoothing parameters in the framework of nonparametric and semiparametric regression. Selection of smoothing parameters is one of the most important issues in this framework and the choice can heavily influence subsequent results. LÄS MER
4. Robust inference of gene regulatory networks : System properties, variable selection, subnetworks, and design of experiments
Sammanfattning : In this thesis, inference of biological networks from in vivo data generated by perturbation experiments is considered, i.e. deduction of causal interactions that exist among the observed variables. Knowledge of such regulatory influences is essential in biology. LÄS MER
5. Protein Mixture Inference as Hitting Set Variants and Linear Algebra Problems
Sammanfattning : This work is dedicated to the problems of protein inference and quantification in bottom-up proteomics, and, in particular, in shotgun proteomics. We adopt a rather classical approach of representing inference problem as a set cover, where proteins are understood as sets of their observations: peptides' masses or sequences. LÄS MER