Search for dissertations about: "likelihood process"

Showing result 1 - 5 of 138 swedish dissertations containing the words likelihood process.

  1. 1. Modelling and Inference for Spatio-Temporal Marked Point Processes

    Author : Ottmar Cronie; Göteborgs universitet; Göteborgs universitet; Gothenburg University; []
    Keywords : NATURVETENSKAP; LANTBRUKSVETENSKAPER; NATURAL SCIENCES; AGRICULTURAL SCIENCES; Asymptotic normality; Consistency; Cox-Ingersoll-Ross process; Diffusion process; Edge correction; Goodness-of-fit; Richards growth function; Growth-interaction process; Immigration-death process; Least squares estimation; Markov process; Maximum likelihood estimation; Open-growth; Spatio-temporal marked point process; Stationarity; Stochastic differential equation; Transition density; Asymptotic normality;

    Abstract : This thesis deals with inference problems related to the growth-interaction process (GI-process). The GI-process is a continuous time spatio-temporal point process with dynamic interacting marks (closed disks), in which the immigration-death process (ID-process) controls the arrivals of new marked points as well as their potential life-times. READ MORE

  2. 2. The unemployment process : studies of search, selection, and social mobility in the labor market

    Author : Tomas Korpi; Aage Sørensen; Stockholms universitet; []
    Keywords : SOCIAL SCIENCES; SAMHÄLLSVETENSKAP; Sociology; Sociologi; Sociology; sociologi;

    Abstract : The purpose of this thesis is to examine some particular aspects of the unemployment process, the process by which the risk of unemployment is distributed within a population. This process can be partitioned into five distinct stages; the initiation of a "negative work career", entry into unemployment, the situation during unemployment, exit from unemployment, and finally the long-term consequences of unemployment for the employment situation of the individual. READ MORE

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

    Author : Mohamed Abdalmoaty; Håkan Hjalmarsson; Jimmy Olsson; KTH; []
    Keywords : ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; TEKNIK OCH TEKNOLOGIER; NATURAL SCIENCES; ENGINEERING AND TECHNOLOGY; 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

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

    Author : Mohamed Abdalmoaty; Håkan Hjalmarsson; Adrian Wills; KTH; []
    Keywords : 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;

    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

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

    Author : Martin Solberger; Rolf Larsson; Johan Lyhagen; Jean-Pieree Urbain; Uppsala universitet; []
    Keywords : 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