Search for dissertations about: "Normal estimation"
Showing result 11 - 15 of 147 swedish dissertations containing the words Normal estimation.
-
11. 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
-
12. Dynamic Power System Load -Estimation of Parameters from Operational Data
Abstract : The significance of load modeling for voltage stability studies has been emphasized by several disturbances, which have taken place in the past years. They have shown that the loads in combination with other dynamics are among the main contributors of prolonged low voltage conditions, voltage instability and collapse in the power system. READ MORE
-
13. Recent Studies on Lp-Norm Estimation
Abstract : When estimating the parameters in a linear regression model, the method of least squares (L^-norm estimator) is often used. When thè residuals are independent and identically normally distributed, the least squares estimator is BLUE as well as equivalent to the maximum likelihood estimator. READ MORE
-
14. Contributions to Estimation and Testing Block Covariance Structures in Multivariate Normal Models
Abstract : This thesis concerns inference problems in balanced random effects models with a so-called block circular Toeplitz covariance structure. This class of covariance structures describes the dependency of some specific multivariate two-level data when both compound symmetry and circular symmetry appear simultaneously. READ MORE
-
15. Studies in Estimation of Patterned Covariance Matrices
Abstract : Many testing, estimation and confidence interval procedures discussed in the multivariate statistical literature are based on the assumption that the observation vectors are independent and normally distributed. The main reason for this is that often sets of multivariate observations are, at least approximately, normally distributed. READ MORE