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The Annals of Statistics, ISSN 0090-5364, 8/2005, Volume 33, Issue 4, pp. 1580 - 1616
Journal Article
Journal of the Korean Statistical Society, ISSN 1226-3192, 03/2013, Volume 42, Issue 1, pp. 9 - 15
Contour regression, a method for estimating the central subspace in regression, is based on estimating contour directions of small variation in the response.... 
Dimension reduction | Contour regression | Central subspace | Local regression | STATISTICS & PROBABILITY | SLICED INVERSE REGRESSION | ASYMPTOTICS | PRINCIPAL HESSIAN DIRECTIONS | 통계학
Journal Article
中国科学:数学英文版, ISSN 1674-7283, 2009, Issue 3, pp. 539 - 560
In this paper, we propose a new estimate for dimension reduction, called the weighted variance estimate (WVE), which includes Sliced Average Variance Estimate... 
average | inverse | subspace | weight | contour | sliced | central | variance | regression | sufficient | function | estimate | reduction | dimension
Journal Article
한국통계학회 학술발표논문집, 2005, Volume 2006, p. 61
Journal Article
The Annals of Statistics, ISSN 0090-5364, 2/2013, Volume 41, Issue 1, pp. 250 - 268
Journal Article
The Annals of Statistics, ISSN 0090-5364, 8/2014, Volume 42, Issue 4, pp. 1657 - 1688
Journal Article
Science in China Series A: Mathematics, ISSN 1006-9283, 3/2009, Volume 52, Issue 3, pp. 539 - 560
Journal Article
Journal of the American Statistical Association, ISSN 0162-1459, 09/2008, Volume 103, Issue 483, pp. 1177 - 1186
Journal Article
Journal of the Royal Statistical Society. Series B (Statistical Methodology), ISSN 1369-7412, 6/2010, Volume 72, Issue 3, pp. 367 - 387
Journal Article
International Statistical Review / Revue Internationale de Statistique, ISSN 0306-7734, 4/2013, Volume 81, Issue 1, pp. 134 - 150
Journal Article
Technometrics, ISSN 0040-1706, 04/2019, Volume 61, Issue 2, pp. 259 - 272
Sufficient dimension reduction (SDR) methods are popular model-free tools for preprocessing and data visualization in regression problems where the number of... 
Sufficient dimension reduction | Central discriminant subspace | Envelope models | Central subspace | Linear discriminant analysis | Quadratic discriminant analysis | STATISTICS & PROBABILITY | SLICED INVERSE REGRESSION | ALGORITHMS
Journal Article
Journal of the Royal Statistical Society. Series B (Statistical Methodology), ISSN 1369-7412, 4/2009, Volume 71, Issue 2, pp. 525 - 548
Journal Article
Biometrics, ISSN 0006-341X, 9/2011, Volume 67, Issue 3, pp. 886 - 895
Journal Article
Communications in Statistics - Simulation and Computation, ISSN 0361-0918, 10/2010, Volume 39, Issue 10, pp. 1868 - 1876
Sliced regression is an effective dimension reduction method by replacing the original high-dimensional predictors with its appropriate low-dimensional... 
Sufficient dimension reduction | Central subspace | Shrinkage estimation | Sliced regression | STATISTICS & PROBABILITY | SLICED INVERSE REGRESSION | REGULARIZATION | VARIABLE SELECTION | Studies | Reduction | Effectiveness | Computer simulation | Mathematical analysis | Regression | Data processing | Mathematical models | Shrinkage | Subspaces
Journal Article
Computational Statistics and Data Analysis, ISSN 0167-9473, 2010, Volume 54, Issue 4, pp. 976 - 986
For semiparametric models, one of the key issues is to reduce the predictors’ dimension so that the regression functions can be efficiently estimated based on... 
NONCONCAVE PENALIZED LIKELIHOOD | NUMBER | COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS | DIMENSION REDUCTION | CENTRAL MEAN SUBSPACE | LASSO | STATISTICS & PROBABILITY | SLICED INVERSE REGRESSION | ASYMPTOTICS | ORACLE PROPERTIES | PRINCIPAL HESSIAN DIRECTIONS
Journal Article
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