Sökning: "Probability and Inference Theory Group"

Visar resultat 1 - 5 av 12 avhandlingar innehållade orden Probability and Inference Theory Group.

1. 1. Statistical inference and time-frequency estimation for non-stationary signal classification

   Författare :Rachele Anderson; Statistical Signal Processing Group; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; Non-stationary processes; stochastic modeling; inference; spectral analysis; time-frequency analysis; classification; biomedical applications; deep learning;

   Sammanfattning : This thesis focuses on statistical methods for non-stationary signals. The methods considered or developed address problems of stochastic modeling, inference, spectral analysis, time-frequency analysis, and deep learning for classification. LÄS MER

3. 2. Random Geometry and Reinforced Jump Processes

   Författare :Tuan-Minh Nguyen; Probability and Inference Theory Group; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; random polygons; products of random matrices; vertex-reinforced jump processes; pseudotrajectories; random walks in simplexes; Markov chains in a general state space;

   Sammanfattning : This thesis comprises three papers studying several mathematical models related to geometric Markov processes and random processes with reinforcements. The main goal of these works is to investigate the dynamics as well as the limiting behaviour of the models as time goes to infinity, the existence of invariant measures and limiting distributions, the speed of convergence and other interesting relevant properties. LÄS MER

4. 3. Modelling and Inference using Locally Stationary Processes : Biomedical applications

   Författare :Rachele Anderson; Statistical Signal Processing Group; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Modelling of Time-Varying Signals; Locally Stationary Processes; Statistical Inference; Time-frequency Estimation; Regression; EEG Signals; HRV Signals;

   Sammanfattning : This thesis considers statistical methods for non-stationary signals, specifically stochastic modelling, inference on the model parameters and optimal spectral estimation. The models are based on Silverman’s definition of Locally Stationary Processes (LSPs). LÄS MER

5. 4. Non-parametric methods for functional data

   Författare :Johan Strandberg; Sara Sjöstedt de Luna; Konrad Abramowicz; Lina Schelin; Charlotte Häger; Pedro Delicado; Umeå universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; functional data analysis; testing; clustering; prediction; inference; bagging Voronoi strategy; kriging; dependency; matematisk statistik; Mathematical Statistics;

   Sammanfattning : In this thesis we develop and study non-parametric methods within three major areas of functional data analysis: testing, clustering and prediction. The thesis consists of an introduction to the field, a presentation and discussion of the three areas, and six papers. LÄS MER

7. 5. Bayesian Cluster Analysis : Some Extensions to Non-standard Situations

   Författare :Jessica Franzén; Daniel Thorburn; Jukka Corander; Stockholms universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Cluster analysis; Clustering; Classification; Mixture model; Gaussian; Bayesian inference; MCMC; Gibbs sampler; Deviant group; Longitudinal; Missing data; Multiple imputation; Statistics; Statistik; Statistics; statistik;

   Sammanfattning : The Bayesian approach to cluster analysis is presented. We assume that all data stem from a finite mixture model, where each component corresponds to one cluster and is given by a multivariate normal distribution with unknown mean and variance. LÄS MER