Sökning: "likelihood estimation"

Visar resultat 1 - 5 av 204 avhandlingar innehållade orden likelihood estimation.

  1. 1. Composite Likelihood Estimation for Latent Variable Models with Ordinal and Continuous, or Ranking Variables

    Författare :Myrsini Katsikatsou; Fan Yang-Wallentin; Irini Moustaki; Karl Gustav Jöreskog; Ruggero Bellio; Uppsala universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; latent variable models; factor analysis; structural equation models; Thurstonian model; item response theory; composite likelihood estimation; pairwise likelihood estimation; maximum likelihood; weighted least squares; ordinal variables; ranking variables; lavaan; Statistics; Statistik;

    Sammanfattning : The estimation of latent variable models with ordinal and continuous, or ranking variables is the research focus of this thesis. The existing estimation methods are discussed and a composite likelihood approach is developed. LÄS MER

  3. 2. DSGE Model Estimation and Labor Market Dynamics

    Författare :Glenn Mickelsson; Nils Gottfries; Karl Walentin; Martin M Andreasen; Uppsala universitet; []
    Nyckelord :SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; DSGE Models; Macroeconomics; Estimation; Uninformative Priors; Maximum Likelihood; Labor Hoarding; US Labor Market; Swedish Micro Data; Economics; Nationalekonomi;

    Sammanfattning : Essay 1: Estimation of DSGE Models with Uninformative PriorsDSGE models are typically estimated using Bayesian methods, but because prior information may be lacking, a number of papers have developed methods for estimation with less informative priors (diffuse priors). This paper takes this development one step further and suggests a method that allows full information maximum likelihood (FIML) estimation of a medium-sized DSGE model. LÄS MER

  4. 3. Identification of Stochastic Nonlinear Dynamical Models Using Estimating Functions

    Författare :Mohamed Abdalmoaty; Håkan Hjalmarsson; Adrian Wills; KTH; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Prediction Error Method; Maximum Likelihood; Data-driven; Learning; Stochastic; Nonlinear; Dynamical Models; Non-stationary Linear Predictors; Intractable Likelihood; Latent Variable Models; Estimation; Process Disturbance; Electrical Engineering; Elektro- och systemteknik;

    Sammanfattning : Data-driven modeling of stochastic nonlinear systems is recognized as a very challenging problem, even when reduced to a parameter estimation problem. A main difficulty is the intractability of the likelihood function, which renders favored estimation methods, such as the maximum likelihood method, analytically intractable. LÄS MER

  5. 4. Learning Stochastic Nonlinear Dynamical Systems Using Non-stationary Linear Predictors

    Författare :Mohamed Abdalmoaty; Håkan Hjalmarsson; Jimmy Olsson; KTH; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; Stochastic Nonlinear Systems; Nonlinear System Identification; Learning Dynamical Models; Maximum Likelihood; Estimation; Process Disturbance; Prediction Error Method; Non-stationary Linear Predictors; Intractable Likelihood; Latent Variable Models; Electrical Engineering; Elektro- och systemteknik;

    Sammanfattning : The estimation problem of stochastic nonlinear parametric models is recognized to be very challenging due to the intractability of the likelihood function. Recently, several methods have been developed to approximate the maximum likelihood estimator and the optimal mean-square error predictor using Monte Carlo methods. LÄS MER

  7. 5. Estimation and Detection with Applications to Navigation

    Författare :David Törnqvist; Fredrik Gustafsson; Hugh Durrant-Whyte; Linköpings universitet; []
    Nyckelord :Navigation; SLAM; Particle Filter; Estimation; TECHNOLOGY; TEKNIKVETENSKAP;

    Sammanfattning : The ability to navigate in an unknown environment is an enabler for truly utonomous systems. Such a system must be aware of its relative position to the surroundings using sensor measurements. It is instrumental that these measurements are monitored for disturbances and faults. LÄS MER