Sökning: "weighted regression"
Visar resultat 1 - 5 av 50 avhandlingar innehållade orden weighted regression.
1. Weighted Regression with Application to Array Antennas
Sammanfattning : A nonlinear system can be modelled with a simple linear model ifthe model is only valid locally. This can be done by assigningweights to the estimation data, as a function of the distance tothe modelled point. The weighting is here used to develop adirection-dependent calibration method for array antennas. LÄS MER
2. Nonlinear Quantile Regression for Longitudinal Data
Sammanfattning : The overall objective of the two papers in this thesis is to examine the properties of the weighted nonlinear quantile regression estimator for the analysis of longitudinal data. To this end, the question of which weights to be used, the bias of the estimator and the possibility to calculate confidence intervals has to be examined. LÄS MER
3. Local and weighted regression. Bias reduction and model validation
Sammanfattning : Nonlinear systems might be estimated, using local linear models. If the estimation data is corrupted by strongly colored noise the local model will have a bias error. In linear system identification the bias error can be reduced by using instrumentalvariable methods. LÄS MER
4. Parameter Estimation for Multisensor Signal Processing : Reduced Rank Regression, Array Processing and MIMO Communications
Sammanfattning : This thesis deals with three estimation problems motivated by spatial signal processing using arrays of sensors. All three problems are approached using tools from estimation theory, including asymptotical analysis of performance and Cramér-Rao lower bound; Monte Carlo methods are used to evaluate small sample performance. LÄS MER
5. Estimation and Inference for Quantile Regression of Longitudinal Data : With Applications in Biostatistics
Sammanfattning : This thesis consists of four papers dealing with estimation and inference for quantile regression of longitudinal data, with an emphasis on nonlinear models.The first paper extends the idea of quantile regression estimation from the case of cross-sectional data with independent errors to the case of linear or nonlinear longitudinal data with dependent errors, using a weighted estimator. LÄS MER