Sökning: "maximum likelihood estimation"
Visar resultat 11 - 15 av 140 avhandlingar innehållade orden maximum likelihood estimation.
11. Likelihood-Based Tests for Common and Idiosyncratic Unit Roots in the Exact Factor Model
Sammanfattning : 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. LÄS MER
12. On Spectral Estimation and Bistatic Clutter Suppression in Radar Systems
Sammanfattning : Target detection serve as one of the primary objectives in a radar system. From observations, contaminated by receiver thermal noise and interference, the processor needs to determine between target absence or target presence in the current measurements. LÄS MER
13. Simulation and Estimation of Diffusion Processes : Applications in Finance
Sammanfattning : Diffusion processes are the most commonly used models in mathematical finance, and are used extensively not only by academics but also practitioners. Nowadays a wide range of models, that can capture many of the effects observed in financial markets, are available. LÄS MER
14. Essays on Estimation Methods for Factor Models and Structural Equation Models
Sammanfattning : This thesis which consists of four papers is concerned with estimation methods in factor analysis and structural equation models. New estimation methods are proposed and investigated.In paper I an approximation of the penalized maximum likelihood (ML) is introduced to fit an exploratory factor analysis model. LÄS MER
15. On Bounds and Asymptotics of Sequential Monte Carlo Methods for Filtering, Smoothing, and Maximum Likelihood Estimation in State Space Models
Sammanfattning : 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. LÄS MER