Search for dissertations about: "likelihood estimation"
Showing result 1 - 5 of 204 swedish dissertations containing the words likelihood estimation.
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1. Composite Likelihood Estimation for Latent Variable Models with Ordinal and Continuous, or Ranking Variables
Abstract : 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. READ MORE
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2. DSGE Model Estimation and Labor Market Dynamics
Abstract : 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. READ MORE
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3. Identification of Stochastic Nonlinear Dynamical Models Using Estimating Functions
Abstract : 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. READ MORE
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4. Learning Stochastic Nonlinear Dynamical Systems Using Non-stationary Linear Predictors
Abstract : 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. READ MORE
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5. Estimation and Detection with Applications to Navigation
Abstract : 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. READ MORE