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Likelihood-Based Sufficient Dimension Reduction. Letters to the Editor
(American Statistical Association, 2010-06)
Discussion of the paper Likelihood based sufficient dimension reduction
LDR: A Package for Likelihood-Based Sufficient Dimension Reduction
(Journal Statistical Software, 2011-03)
We introduce a new MATLAB software package that implements several recently proposed likelihood-based methods for sufficient dimension reduction. Current capabilities include estimation of reduced subspaces with a fixed ...
Dimensionality reduction via an orthogonal autoencoder approach for hyperspectral image classification
(The International Society for Photogrammetry and Remote SensingDE, 2020)
Nowadays, the increasing amount of information provided by hyperspectral sensors requires optimal solutions to ease the subsequent analysis of the produced data. A common issue in this matter relates to the hyperspectral ...
Estimating sufficient reductions of the predictors in abundant high-dimensional regressions
(Institute of Mathematical Statistics, 2012-02)
We study the asymptotic behavior of a class of methods for sufficient dimension reduction in high-dimension regressions, as the sample size and number of predictors grow in various alignments. It is demonstrated that these ...
Selection of variables and dimension reduction in high-dimensional non-parametric regression
(INST MATHEMATICAL STATISTICS, 2008)
Sufficient Reductions in Regressions with Exponential Family Inverse Predictors
(American Statistical Association, 2016-07)
We develop methodology for identifying and estimating sufficient reductions in regressions with predictors that, given the response, follow a multivariate exponential family distribution. This setup includes regressions ...
Selection of variables and dimension reduction in high-dimensional non-parametric regressionELECTRONIC JOURNAL OF STATISTICS
(INST MATHEMATICAL STATISTICS, 2016)
Big data and partial least-squares prediction
(Wiley Blackwell Publishing, Inc, 2018-03)
We give a commentary on the challenges of big data for Statistics. We then narrow our discussion to one of those challenges: dimension reduction. This leads to consideration of one particular dimension reduction method—partial ...
Fractal dimension in the evaluation of different treatments of muscular injury in rats
(2018-10-01)
Objectives: To evaluate alterations from different therapies in muscular injury using the Fractal Dimension (FD) method. Methods: 35 animals were allocated in Control Group (C), Injury Control Group (IC), Injury Low Level ...