Search for dissertations about: "principal components regression"

Showing result 1 - 5 of 27 swedish dissertations containing the words principal components regression.

2. 1. Regression methods in multidimensional prediction and estimation

   Author : Anders Björkström; Rolf Sundberg; Philip J Brown; Stockholms universitet; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; regression; prediction; principal compnents regression; ridge regression; partial least squares; Mathematical statistics; Matematisk statistik; matematisk statistik; Mathematical Statistics;

   Abstract : 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. READ MORE

4. 2. Aspects of common principal components

   Author : Toni Duras; Thomas Holgersson; Jönköping University; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES;

   Abstract : 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. READ MORE

5. 3. Bilinear Regression and Second Order Calibration

   Author : Marie Linder; Pieter Kroonenberg; Stockholms universitet; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; chemometrics; calibration; multivariate; hyphenated methods; matrix data; bilinear model; least squares; singular value decomposition; generalized rank annihilation; trilinear decomposition; parallel factor analysis; principal components regression; partial least squares; prediction; matematisk statistik; Mathematical Statistics;

   Abstract : 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. READ MORE

6. 4. Essays on Panel Data with Multidimensional Unobserved Heterogeneity

   Author : Yana Petrova; Nationalekonomiska institutionen; []
   Keywords : SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; Econometrics; Factor-Augmented Panel Regression; Interactive Effects; Unknown Factors; CCE Estimation; Principal Components;

   Abstract : 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. READ MORE

7. 5. Statistical Methods for Designed Experiments and Spectroscopic Data

   Author : Tobias Adolfsson; Göteborgs universitet; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; saturated orthogonal designs; multiple inference; step-down testing; partial least squares; principal components regression; multiple inference;

   Abstract : 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. READ MORE