Buscar
Mostrando ítems 1-10 de 3074
Likelihood-Based Sufficient Dimension Reduction. Letters to the Editor
(American Statistical Association, 2010-06)
Discussion of the paper Likelihood based sufficient dimension reduction
Sucient dimension reduction and prediction in regression: Asymptotic results
(Elsevier Inc, 2019-03)
We consider model-based sufficient dimension reduction for generalized linear models and prove the consistency and asymptotic normality of the prediction estimator studied empirically for the normal case by Adragni and ...
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 ...
Belokurov-usyukina loop reduction in non-integer dimensionbelokurov-usyukina loop reduction in non-integer dimension
(AMERICAN INSTITUTE OF PHYSICS, 2013)
A projection pursuit framework for supervised dimension reduction of high dimensional small sample datasets
(ElsevierAmsterdam, 2015-02)
The analysis and interpretation of datasets with large number of features and few examples has remained as a challenging problem in the scientific community, owing to the difficulties associated with the curse-of-the-dim ...
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 ...