Publication date
June 2008
DOI Publisher
Informa UK Limited ISSN
0162-1459 Citation count (estimate)
63Abstract
10.1198/016214508000000418Journal of the American Statistical Association103482811-82
10.1198/016214508000000418Journal of the American Statistical Association103482811-82
Dimension reduction in a regression analysis of response y given a p-dimensional vector of predictor...
We employ Lasso shrinkage within the context of sufficient dimension reduction to obtain a shrinkage...
10.1198/jasa.2009.tm09372Journal of the American Statistical Association105489278-29
[[sponsorship]]統計科學研究所[[note]]已出版;[SCI];有審查制度;不具代表性[[note]]http://gateway.isiknowledge.com/gateway/G...
In statistics, dimension reduction is a method to reduce the number of variables, which will then be...
Regression is the study of the dependence of a response variable y on a collection predictors p coll...
[[sponsorship]]統計科學研究所[[note]]已出版;[SCI];有審查制度;具代表性[[note]]http://gateway.isiknowledge.com/gateway/Ga...
Without parametric assumptions, high-dimensional regression analy-sis is already complex. This is ma...
The presented work deals with Sliced inverse regression method for dimension reduction of explanator...
Summary. Sliced inverse regression is one of the widely used dimension reduction methods. Chiaromont...
Sliced inverse regression is one of the widely used dimension reduction methods. Chiaromonte and co-...
A new method is developed for performing sufficient dimension reduction when probabilistic graphical...
By slicing the region of the response (Li, 1991, SIR) and applying local ker-nel regression (Xia et ...
Sliced Inverse Regression is a method for reducing the dimensionality in multivariate non parametric...
The big data era poses great challenges as well as opportunities for researchers to develop efficien...
Dimension reduction in a regression analysis of response y given a p-dimensional vector of predictor...
We employ Lasso shrinkage within the context of sufficient dimension reduction to obtain a shrinkage...
10.1198/jasa.2009.tm09372Journal of the American Statistical Association105489278-29
[[sponsorship]]統計科學研究所[[note]]已出版;[SCI];有審查制度;不具代表性[[note]]http://gateway.isiknowledge.com/gateway/G...
In statistics, dimension reduction is a method to reduce the number of variables, which will then be...
Regression is the study of the dependence of a response variable y on a collection predictors p coll...
[[sponsorship]]統計科學研究所[[note]]已出版;[SCI];有審查制度;具代表性[[note]]http://gateway.isiknowledge.com/gateway/Ga...
Without parametric assumptions, high-dimensional regression analy-sis is already complex. This is ma...
The presented work deals with Sliced inverse regression method for dimension reduction of explanator...
Summary. Sliced inverse regression is one of the widely used dimension reduction methods. Chiaromont...
Sliced inverse regression is one of the widely used dimension reduction methods. Chiaromonte and co-...
A new method is developed for performing sufficient dimension reduction when probabilistic graphical...
By slicing the region of the response (Li, 1991, SIR) and applying local ker-nel regression (Xia et ...
Sliced Inverse Regression is a method for reducing the dimensionality in multivariate non parametric...
The big data era poses great challenges as well as opportunities for researchers to develop efficien...
Dimension reduction in a regression analysis of response y given a p-dimensional vector of predictor...
We employ Lasso shrinkage within the context of sufficient dimension reduction to obtain a shrinkage...
10.1198/jasa.2009.tm09372Journal of the American Statistical Association105489278-29
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