Generalized Canonical Regression
نویسندگان
چکیده
منابع مشابه
Generalized Canonical Variables
Often the random vector variable, X, being encountered, for example, in atmospheric, biological, economic and environmental and other research, is of a large dimension but admits of meaningful grouping(s) into two or more mutually exclusive and exhaustive subvectors. Dimension reduction techniques are then sought to obtain “representative” new variables for each group to be formed by taking sui...
متن کاملGeneralized Ridge Regression Estimator in Semiparametric Regression Models
In the context of ridge regression, the estimation of ridge (shrinkage) parameter plays an important role in analyzing data. Many efforts have been put to develop skills and methods of computing shrinkage estimators for different full-parametric ridge regression approaches, using eigenvalues. However, the estimation of shrinkage parameter is neglected for semiparametric regression models. The m...
متن کاملThe Canonical Generalized Polar Decomposition
The polar decomposition of a square matrix has been generalized by several authors to scalar products on Rn or Cn given by a bilinear or sesquilinear form. Previous work has focused mainly on the case of square matrices, sometimes with the assumption of a Hermitian scalar product. We introduce the canonical generalized polar decomposition A = WS, defined for general m × n matrices A, where W is...
متن کاملKernel Generalized Canonical Correlation Analysis
A classical problem in statistics is to study relationships between several blocks of variables. The goal is to find variables of one block directly related to variables of other blocks. The Regularized Generalized Canonical Correlation Analysis (RGCCA) is a very attractive framework to study such a kind of relationships between blocks. However, RGCCA captures linear relations between blocks an...
متن کاملDeep Generalized Canonical Correlation Analysis
We present Deep Generalized Canonical Correlation Analysis (DGCCA) – a method for learning nonlinear transformations of arbitrarily many views of data, such that the resulting transformations are maximally informative of each other. While methods for nonlinear two-view representation learning (Deep CCA, (Andrew et al., 2013)) and linear many-view representation learning (Generalized CCA (Horst,...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: SSRN Electronic Journal
سال: 2007
ISSN: 1556-5068
DOI: 10.2139/ssrn.1003174