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Principal component models for sparse functional data
Functional data analysis Principal components Mixed effects model Reduced rank estimation Growth curve
2015/8/21
The elements of a multivariate data set are often curves rather than single points. Functional principal components can be used to describe the modes of variation of such curves. If one has complete m...
Sparse Principal Component Analysis
Arrays Gene expression Lasso/elastic net Multivariate analysis Singular value decomposition Thresholding
2015/8/21
Principal component analysis (PCA) is widely used in data processing and dimensionality reduction. However,PCA suffers from the fact that each principal component is a linear combination of all the or...
Independent component analysis via nonparametric maximum likelihood estimation
Blind source separation density estimation independent component analysis log-concave projection
2012/6/19
Independent Component Analysis (ICA) models are very popular semiparametric models in which we observe independent copies of a random vector $X = AS$, where $A$ is a non-singular matrix and $S$ has in...
A 2-component $\mu$-Hunter-Saxton equation
Mathematical Physics (math-ph) Exactly Solvable and Integrable Systems (nlin.SI)
2010/11/10
In this paper, we propose a two-component generalization of the generalized Hunter-Saxton equation obtained in \cite{BLG2008}. We will show that this equation is a bihamiltonian Euler equation, and al...