Sökning: "Likelihood based methods"

Visar resultat 11 - 15 av 237 avhandlingar innehållade orden Likelihood based methods.

1. 11. On Bounds and Asymptotics of Sequential Monte Carlo Methods for Filtering, Smoothing, and Maximum Likelihood Estimation in State Space Models

   Författare :Jimmy Olsson; Matematisk statistik; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; actuarial mathematics; programming; operations research; Statistics; Matematik; Mathematics; state space models; smoothing; sequential Monte Carlo; particle filter; EM algorithm; maximum likelihood; consistency; Asymptotic normality; Statistik; operationsanalys; programmering; aktuariematematik;

   Sammanfattning : This thesis is based on four papers (A-D) treating filtering, smoothing, and maximum likelihood (ML) estimation in general state space models using stochastic particle filters (also referred to as sequential Monte Carlo (SMC) methods). The aim of Paper A is to study the bias of Monte Carlo integration estimates produced by the so-called bootstrap particle filter. LÄS MER

3. 12. COPD in primary care : exploring conditions for implementation of evidence-based interventions and eHealth

   Författare :Sara Lundell; Karin Wadell; Börje Rehn; Åsa Holmner; Maria Wiklund; Lisa Skär; Umeå universitet; []
   Nyckelord :MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; COPD; primary care; implementation; eHealth; qualitative; mixed methods; meta-analysis; KOL; primärvård; implementering; eHälsa; Kvalitativ; mixad metod; metaanalys; sjukgymnastik; Physiotherapy;

   Sammanfattning : Chronic obstructive pulmonary disease (COPD) is a major public health problem. Symptoms and comorbidities associated with COPD affect the whole body. Clinical guidelines for COPD recommend pulmonary rehabilitation (PR) including exercise training and education promoting self-management strategies. LÄS MER

4. 13. Analysis of Some Methods for Identifying Dynamic Errors-in-variables Systems

   Författare :Mei Hong; Torsten Söderström; Magnus Jansson; Uppsala universitet; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; system identification; errors-in-variables; least squares; instrumental variable; maximum likelihood; bias compensated least squares; bias eliminating least squares; Frisch scheme; higher-order statistics; accuracy analysis; periodic data; Signal processing; Signalbehandling;

   Sammanfattning : A system where errors or noises are present on both the inputs and the outputs is called an errors-in-variables (EIV) system. EIV systems appear in industrial and agricultural processes, medical sciences, economical systems, biotechnology, as well as in many other areas. LÄS MER

5. 14. Maximum spacing methods and limit theorems for statistics based on spacings

   Författare :Magnus Ekström; Umeå universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Estimation; spacings; maximum spacing method; consistency; ^-divergence; goodness of fit; unimodal density; entropy estimation; uniform distribution;

   Sammanfattning : The maximum spacing (MSP) method, introduced by Cheng and Amin (1983) and independently by Ranneby (1984), is a general estimation method for continuous univariate distributions. The MSP method, which is closely related to the maximum likelihood (ML) method, can be derived from an approximation based on simple spacings of the Kullback-Leibler information. LÄS MER

7. 15. On risk-coherent input design and Bayesian methods for nonlinear system identification

   Författare :Patricio E. Valenzuela Pacheco; Cristian Rojas; Daniel Rivera; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; System identification; input design; Bayesian methods; nonlinear models; risk theory; Electrical Engineering; Elektro- och systemteknik;

   Sammanfattning : System identification deals with the estimation of mathematical models from experimental data. As mathematical models are built for specific purposes, ensuring that the estimated model represents the system with sufficient accuracy is a relevant aspect in system identification. LÄS MER