Search for dissertations about: "Icke-parametriska metoder"

Showing result 1 - 5 of 11 swedish dissertations containing the words Icke-parametriska metoder.

2. 1. Non-parametric methods for functional data

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

   Abstract : 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. READ MORE

4. 2. Monotonic and Semiparametric Regression for the Detection of Trends in Environmental Quality Data

   Author : Mohamed Hussian; Anders Grimvall; Ali Hadi; Linköpings universitet; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; Normalisation; Monotonic; Semiparametric; Temporal trends; fluctuations; global; local; Matematisk statistik; Icke-parametriska metoder; Statistics; Statistik;

   Abstract : Natural fluctuations in the state of the environment can long conceal or distort important trends in the human impact on our ecosystems. Accordingly, there is increasing interest in statistical normalisation techniques that can clarify the anthropogenic effects by removing meteorologically driven fluctuations and other natural variation in time series of environmental quality data. READ MORE

5. 3. System Identification with Multi-Step Least-Squares Methods

   Author : Miguel Galrinho; Håkan Hjalmarsson; Manfred Deistler; KTH; []
   Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Electrical Engineering; Elektro- och systemteknik;

   Abstract : The purpose of system identification is to build mathematical models for dynam-ical systems from experimental data. With the current increase in complexity of engineering systems, an important challenge is to develop accurate and computa-tionally simple algorithms, which can be applied in a large variety of settings. READ MORE

6. 4. On Symmetries and Metrics in Geometric Inference

   Author : Giovanni Luca Marchetti; Danica Kragic; Anastasiia Varava; Emanuele Rodolà; KTH; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; Machine Learning; Computational Geometry; Voronoi; Delaunay; Symmetry; Equivariance; Datalogi; Computer Science;

   Abstract : Spaces of data naturally carry intrinsic geometry. Statistics and machine learning can leverage on this rich structure in order to achieve efficiency and semantic generalization. Extracting geometry from data is therefore a fundamental challenge which by itself defines a statistical, computational and unsupervised learning problem. READ MORE

7. 5. Development and Application of Uncertainty Analysis Approaches for MELCOR Simulations of Severe Accidents

   Author : Wanhong Wang; Weimin Ma; Florian Fichot; KTH; []
   Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Severe accident; MELCOR; uncertainty analysis; Wilks’ method; Bootstrapped artificial neural network; deterministic sampling method; 95 95 tolerance limit.; Svåra haverier; MELCOR; osäkerhetsanalys; Wilks’ metod; artificiella neuronnät; deterministiska urvalsmetoder; 95 95-toleransgränser.;

   Abstract : The contemporary needs in advancing safety analysis methods and the increasing stringency in light water reactor (LWR) safety in the post-Fukushima era require more advanced and systematical approaches for severe accident analyses. The best estimate plus uncertainty (BEPU) methods are among such approaches and have been widely used for deterministic safety analysis (DSA) of design basis accidents (DBAs). READ MORE