Sökning: "Gaussian Markov random fields"

Visar resultat 6 - 9 av 9 avhandlingar innehållade orden Gaussian Markov random fields.

  1. 6. Spatial inference for non-lattice data using Markov Random fields

    Författare :Linda Werner Hartman; Matematisk statistik; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES;

    Sammanfattning : This thesis deals with how computationally effective lattice models could be used for inference of data with a continuous spatial index. The fundamental idea is to approximate a Gaussian field with a Gaussian Markov random field (GMRF) on a lattice. LÄS MER

  2. 7. Spatial Statistics and Ancestral Recombination Graphs with Applications in Gene Mapping and Geostatistics

    Författare :Linda Werner Hartman; Matematisk statistik; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Genetik; Genetics; cytogenetics; cytogenetik; genetic association analysis; ancestral recombination graph Generalized linear mixed models; kriging; bilinear interpolation; Gaussian Markov random fields; Statistics;

    Sammanfattning : This thesis explores models and algorithms in geostatistics and gene mapping. The first part deals with the use of computationally effective lattice models for inference of data with a continuous spatial index. LÄS MER

  3. 8. Stochastic Models Involving Second Order Lévy Motions

    Författare :Jonas Wallin; Matematisk statistik; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES;

    Sammanfattning : This thesis is based on five papers (A-E) treating estimation methods for unbounded densities, random fields generated by Lévy processes, behavior of Lévy processes at level crossings, and a Markov random field mixtures of multivariate Gaussian fields. In Paper A we propose an estimator of the location parameter for a density that is unbounded at the mode. LÄS MER

  4. 9. Computationally efficient methods in spatial statistics : Applications in environmental modeling

    Författare :David Bolin; Matematisk statistik; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES;

    Sammanfattning : In this thesis, computationally efficient statistical models for large spatial environmental data sets are constructed. In the first part of the thesis, a method for estimating spatially dependent temporal trends is developed. A space-varying regression model, where the regression coefficients for the spatial locations are dependent, is used. LÄS MER