Sökning: "principal components regression"
Visar resultat 1 - 5 av 27 avhandlingar innehållade orden principal components regression.
1. Regression methods in multidimensional prediction and estimation
Sammanfattning : In regression with near collinear explanatory variables, the least squares predictor has large variance. Ordinary least squares regression (OLSR) often leads to unrealistic regression coefficients. Several regularized regression methods have been proposed as alternatives. LÄS MER
2. Aspects of common principal components
Sammanfattning : The focus of this thesis is the common principal component (CPC) model, the generalization of principal components to several populations. Common principal components refer to a group of multidimensional datasets such that their inner products share the same eigenvectors and are therefore simultaneously diagonalized by a common decorrelator matrix. LÄS MER
3. Bilinear Regression and Second Order Calibration
Sammanfattning : We consider calibration of second-order (or "hyphenated") instruments for chemical analysis. Many such instruments generate bilinear two-way (matrix) type data for each specimen. The bilinear regression model is to be estimated from a number of specimens of known composition. LÄS MER
4. Essays on Panel Data with Multidimensional Unobserved Heterogeneity
Sammanfattning : This thesis contributes to econometric methodology in terms of estimation and inference in static panel data models with unobserved multidimensional heterogeneity. When not properly accounted for, unobserved heterogeneity may introduce bias into the parameter estimates associated with covariates of interest, such as treatment indicators or determinants of macroeconomic indicators. LÄS MER
5. Statistical Methods for Designed Experiments and Spectroscopic Data
Sammanfattning : This thesis consists of six papers related to saturated orthogonal designs, spectroscopic and high dimension data analysis. The first two papers deals with testing procedures for saturated orthogonal designs. Both the presented methods controls the multiple level of significance. LÄS MER