Sökning: "MATEMATIK Tillämpad matematik Matematisk statistik"

Visar resultat 11 - 15 av 18 avhandlingar innehållade orden MATEMATIK Tillämpad matematik Matematisk statistik.

1. 11. Bayesian inference in probabilistic graphical models

   Författare :Felix Leopoldo Rios; Tatjana Pavlenko; Alun Thomas; KTH; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Graphical models; Bayesian inference; predictive classification; decomposable graphs; Tillämpad matematik och beräkningsmatematik; Applied and Computational Mathematics;

   Sammanfattning : This thesis consists of four papers studying structure learning and Bayesian inference in probabilistic graphical models for both undirected and directed acyclic graphs (DAGs).Paper A presents a novel algorithm, called the Christmas tree algorithm (CTA), that incrementally construct junction trees for decomposable graphs by adding one node at a time to the underlying graph. LÄS MER

3. 12. Bayesian structure learning in graphical models

   Författare :Felix Leopoldo Rios; Tatjana Pavlenko; Klas Markström; KTH; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Bayesian statistics; graphical models; Bayesian networks; Markov networks; structure learning; Tillämpad matematik och beräkningsmatematik; Applied and Computational Mathematics;

   Sammanfattning : This thesis consists of two papers studying structure learning in probabilistic graphical models for both undirected graphs anddirected acyclic graphs (DAGs).Paper A, presents a novel family of graph theoretical algorithms, called the junction tree expanders, that incrementally construct junction trees for decomposable graphs. LÄS MER

4. 13. On particle-based online smoothing and parameter inference in general state-space models

   Författare :Johan Westerborn; Jimmy Olsson; Sumeetpal Singh; KTH; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Tillämpad matematik och beräkningsmatematik; Applied and Computational Mathematics;

   Sammanfattning : This thesis consists of 4 papers, presented in Paper A-D, on particle- based online smoothing and parameter inference in general state-space hidden Markov models.In Paper A a novel algorithm, the particle-based, rapid incremental smoother (PaRIS), aimed at efficiently performing online approxima- tion of smoothed expectations of additive state functionals in general hidden Markov models, is presented. LÄS MER

5. 14. Weak Convergence of First-Rare-Event Times for Semi-Markov Processes

   Författare :Myroslav Drozdenko; Dmitrii Silvestrov; Raimondo Manca; Mälardalens högskola; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; weak convergence; first-rare-event times; semi-Markov processes; Mathematical statistics; Matematisk statistik; Matematik tillämpad matematik;

   Sammanfattning : I denna avhandling studerar vi nödvändiga och tillräckliga villkor för svag konvergens av första-sällan-händelsetider för semi-Markovska processer.I introduktionen ger vi nödvändiga grundläggande definitioner och beskrivningar av modeller som betraktas i avhandlingen, samt ger några exempel på situationer i vilka metoder av första-sällan-händelsetider kan vara lämpliga att använda. LÄS MER

7. 15. Nonlinearly Perturbed Renewal Equations : asymptotic Results and Applications

   Författare :Ying Ni; Dmitrii Silvestrov; Anatoliy Malyarenko; Mats Gyllenberg; Mälardalens högskola; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Nonlinearly perturbed renewal equation; perturbed renewal equation; nonlinear perturbation; non-polynomial perturbation; perturbed risk process; perturbed storage process; Mathematical statistics; Matematisk statistik; Mathematics Applied Mathematics; matematik tillämpad matematik;

   Sammanfattning : In this thesis we investigate a model of nonlinearly perturbed continuous-time renewal equation. Some characteristics of the renewal equation are assumed to have non-polynomial perturbations, more specifically they can be expanded with respect to a non-polynomial asymptotic scale. LÄS MER