Search for dissertations about: "maximum likelihood"

Showing result 1 - 5 of 209 swedish dissertations containing the words maximum likelihood.

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

    University dissertation from Uppsala : Acta Universitatis Upsaliensis

    Author : Myrsini Katsikatsou; Uppsala universitet.; [2013]
    Keywords : 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;

    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

  2. 2. Likelihood-Based Tests for Common and Idiosyncratic Unit Roots in the Exact Factor Model

    University dissertation from Uppsala : Acta Universitatis Upsaliensis

    Author : Martin Solberger; Uppsala universitet.; [2013]
    Keywords : SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; panel unit root; dynamic factors; maximum likelihood; Lagrange multiplier; likelihood ratio; factor analysis; Statistics; Statistik;

    Abstract : Dynamic panel data models are widely used by econometricians to study over time the economics of, for example, people, firms, regions, or countries, by pooling information over the cross-section. Though much of the panel research concerns inference in stationary models, macroeconomic data such as GDP, prices, and interest rates are typically trending over time and require in one way or another a nonstationary analysis. READ MORE

  3. 3. Likelihood-Based Panel Unit Root Tests for Factor Models

    University dissertation from Uppsala : Acta Universitatis Upsaliensis

    Author : Xingwu Zhou; Uppsala universitet.; [2014]
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Panel unit root; Exact factor model; Dynamic factor model; Maximum likelihood; Principal components; Lagrange multiplier;

    Abstract : The thesis consists of four papers that address likelihood-based unit root tests for panel data with cross-sectional dependence arising from common factors.In the first three papers, we derive Lagrange multiplier (LM)-type tests for common and idiosyncratic unit roots in the exact factor models based on the likelihood function of the differenced data. READ MORE

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

    University dissertation from Stockholm, Sweden : KTH Royal Institute of Technology

    Author : Mohamed Abdalmoaty; KTH.; [2017]
    Keywords : 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;

    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

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

    University dissertation from Lund University

    Author : Jimmy Olsson; Lunds universitet.; Lund University.; [2007]
    Keywords : 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;

    Abstract : 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. READ MORE