Search for dissertations about: "probability density function"

Showing result 1 - 5 of 95 swedish dissertations containing the words probability density function.

  1. 1. Modelling and Inference for Spatio-Temporal Marked Point Processes

    Author : Ottmar Cronie; Göteborgs universitet; []
    Keywords : LANTBRUKSVETENSKAPER; AGRICULTURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Asymptotic normality; Consistency; Cox-Ingersoll-Ross process; Diffusion process; Edge correction; Goodness-of-fit; Richards growth function; Growth-interaction process; Immigration-death process; Least squares estimation; Markov process; Maximum likelihood estimation; Open-growth; Spatio-temporal marked point process; Stationarity; Stochastic differential equation; Transition density; Asymptotic normality;

    Abstract : This thesis deals with inference problems related to the growth-interaction process (GI-process). The GI-process is a continuous time spatio-temporal point process with dynamic interacting marks (closed disks), in which the immigration-death process (ID-process) controls the arrivals of new marked points as well as their potential life-times. READ MORE

  2. 2. Nonparametric Functional Estimation under Order Restrictions

    Author : Dragi Anevski; Matematisk statistik; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; monotonicity; convexity; deconvolution; kernel smoothing; NPMLE; long range dependence; greatest convex minorant; mixing; Density estimation; limit distribution.; regression; Mathematics; Matematik;

    Abstract : This thesis consists of three papers (Papers A-C) on problems in nonparametric functional estimation, in particular density and regression function estimation and deconvolution, under order assumptions. Pointwise limit distribution results are stated for the obtained estimators, which include isotonic regression estimates, nonparametric maximum likelihood estimates of monotone densities, estimates of convex regression and density functions and deconvolution estimates. READ MORE

  3. 3. Mathematical Modeling of Turbulent Reactive Flows

    Author : Mikael Mortensen; Chalmers tekniska högskola; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; PMF; CFD; probability density function; chemical reactions; presumed mapping function; PDF; conditional moment closure; turbulent mixing; computational fluid dynamics; CMC;

    Abstract : The purpose of this thesis has been to study and develop mathematical models of non-premixed turbulent reacting flows. The models developed can be used both by the chemical process industry and for turbulent combustion applications. Furthermore, the models are general and not developed for any specific chemical or mechanical system. READ MORE

  4. 4. Order restricted inference over countable preordered sets. Statistical aspects of neutron detection

    Author : Vladimir Pastukhov; Matematisk statistik; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Constrained inference; Isotonic regression; Density estimation; Grenander estimator; Limit distribution; Neutron detection;

    Abstract : This thesis consists of four papers. In the first paper, we study the isotonic regression estimator over a general countable preordered set. We obtain the limiting distribution of the estimator and study its properties. Also, it is shown that the isotonisation preserves the rate of convergence of the underlying estimator. READ MORE

  5. 5. Bayesian Modeling of Conditional Densities

    Author : Feng Li; Mattias Villani; Sylvia Frühwirth-Schnatter; Stockholms universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Bayesian inference; Density estimation; smooth mixtures; surface regression; copulas; Markov chain Monte Carlo; Statistics; statistik;

    Abstract : This thesis develops models and associated Bayesian inference methods for flexible univariate and multivariate conditional density estimation. The models are flexible in the sense that they can capture widely differing shapes of the data. The estimation methods are specifically designed to achieve flexibility while still avoiding overfitting. READ MORE