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Multivariate Regression Shrinkage and Selection by Canonical Correlation Analysis
Adaptive Lasso Canonical Correlation Analysis Multivariate Regression
2016/1/25
The problem of regression shrinkage and selection for multivariate regression is considered. The goal is to consistently identify those variables relevant for regression. This is done not only for pre...
Analysis of elliptical copula correlation factor model with Kendall's tau
Elliptical copula correlation matrix factor model Kendall’s tau nuclear norm penalty oracle inequality primal-dual certificate
2013/6/14
We study a factor model for the correlation matrix $\Sigma\in\RR^{d\times d}$ of an elliptical copula. The correlations are connected to Kendall's tau and a natural estimation procedure is to plug-in ...
On near(est) correlation matrix
Correlation matrix positive semidefinite matrix matrix nearness problem versal deformations of matrices
2013/4/27
We present an elementary heuristic reasoning based on Arnold's theory of versal deformations in support of a straightforward algorithm for finding a correlation matrix near the given symmetric one.
Predictive Correlation Screening: Application to Two-stage Predictor Design in High Dimension
Predictive Correlation Screening Application Two-stage Predictor Design High Dimension
2013/4/27
We introduce a new approach to variable selection, called Predictive Correlation Screening, for predictor design. Predictive Correlation Screening (PCS) implements false positive control on the select...
On the spatial correlation between areas of high coseismic slip and aftershock clusters of the Maule earthquake Mw=8.8
Nonparametric clustering Kernel density estimation Maule 2010 Earthquake aftershock distribution slip model.
2012/9/17
We study the spatial distribution of clusters associated to the aftershocks of the megathrust Maule earthquakeMW8.8 of 27 February 2010. We used a recent clustering method which hinges on a nonparamet...
On the spatial correlation between areas of high coseismic slip and aftershock clusters of the Maule earthquake Mw=8.8
Nonparametric clustering Kernel density estimation Maule 2010 Earthquake aftershock distribution slip model.
2012/9/17
We study the spatial distribution of clusters associated to the aftershocks of the megathrust Maule earthquakeMW8.8 of 27 February 2010. We used a recent clustering method which hinges on a nonparamet...
Fast Planar Correlation Clustering for Image Segmentation
Fast Planar Correlation Clustering Image Segmentation
2012/9/18
We describe a new optimization scheme for nding high-quality clusterings in planar graphs that uses weighted perfect matching as a subroutine. Our method provides lower-bounds on the energy of the op...
A higher order correlation unscented Kalman filter
Sequential Parameter Estimation Nonlinear Systems Unscented Kalman Filter Continuous-discrete State Space Estimation of Uncorrelated States Volatility Estimation
2012/9/19
Many nonlinear extensions of the Kalman filter, e.g., the extended and the unscented Kalman filter, reduce the state densities to Gaussian densities. This approximation gives sufficient results in man...
On the Weakenesses of Correlation Measures used for Search Engines' Results (Unsupervised Comparison of Search Engine Rankings)
Search Engines Correlation Measures Search Engine Rankings
2011/7/19
The correlation of the result lists provided by search engines is fundamental and it has deep and multidisciplinary ramifications. Here, we present automatic and unsupervised methods to assess whether...
Efficient Emulators of Computer Experiments Using Compactly Supported Correlation Functions, With an Application to Cosmology
Efficient Emulators Correlation Functions Cosmology
2011/7/19
Statistical emulators of computer simulators have proven to be useful in a variety of applications. The widely adopted model for emulator building, using a Gaussian process model with strictly positiv...
A method for generating realistic correlation matrices
method generating realistic correlation matrices
2011/7/6
Simulating sample correlation matrices is important in many areas of statistics. Approaches such as generating normal data and finding their sample correlation matrix or generating random uniform $[-1...
A flexible observed factor model with separate dynamics for the factor volatilities and their correlation matrix
Correlated factors Inverse Wishart Markov chain Monte Carlo
2011/7/5
Our article considers a regression model with observed factors. The observed factors have a flexible stochastic volatility structure that has separate dynamics for the volatilities and the correlation...
Life time of correlation between stocks prices on established and emerging markets
Life time of correlation correlation coefficient price history stocks
2011/6/21
The correlation coefficient between stocks depends on price history and
includes information on hierarchical structure in financial markets. It is
useful for portfolio selection and estimation of ri...
Constrained probability distributions of correlation functions
cosmology gravitational lensing large scale structure of the Universe galaxies statistics Methods statistical
2011/6/21
Two-point correlation functions are used throughout cosmology as a measure for the statistics of random fields. When used
in Bayesian parameter estimation, their likelihood function is usually replac...
Exploiting Correlation in Sparse Signal Recovery Problems: Multiple Measurement Vectors, Block Sparsity, and Time-Varying Sparsity
Multiple Measurement Vectors Block Sparsity Time-Varying Sparsity
2011/6/16
A trend in compressed sensing (CS) is to exploit struc-
ture for improved reconstruction performance. In the
basic CS model (i.e. the single measurement vec-
tor model), exploiting the clustering s...