Sökning: "Maximum Likelihood Estimation"
Visar resultat 1 - 5 av 132 avhandlingar innehållade orden Maximum Likelihood Estimation.
1. Composite Likelihood Estimation for Latent Variable Models with Ordinal and Continuous, or Ranking Variables
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
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
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
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
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