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Jianqing Fan

Showing results (21-30 of 123) with videos related to

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Stochastic Processes and Their Applications|June 27, 2022
Adaptive Huber Regression on Markov-dependent DataJianqing Fan, Yongyi Guo, Bai Jiang
Annals of Statistics|July 26, 2021
ASYMMETRY HELPS: EIGENVALUE AND EIGENVECTOR ANALYSES OF ASYMMETRICALLY PERTURBED LOW-RANK MATRICESYuxin Chen, Chen Cheng, Jianqing Fan
Journal of Machine Learning Research : JMLR|May 24, 2011
Ultrahigh dimensional feature selection: beyond the linear modelJianqing Fan, Richard Samworth, Yichao Wu
Journal of the Royal Statistical Society. Series B, Statistical Methodology|May 19, 2011
Penalized Composite Quasi-Likelihood for Ultrahigh-Dimensional Variable SelectionJelena Bradic, Jianqing Fan, Weiwei Wang
Journal of the American Statistical Association|January 27, 2012
Nonparametric Independence Screening in Sparse Ultra-High Dimensional Additive ModelsJianqing Fan, Yang Feng, Rui Song
Annals of Statistics|June 5, 2012
HIGH DIMENSIONAL COVARIANCE MATRIX ESTIMATION IN APPROXIMATE FACTOR MODELSJianqing Fan, Yuan Liao, Martina Mincheva
Journal of the American Statistical Association|August 27, 2009
Analysis of Longitudinal Data with Semiparametric Estimation of Covariance FunctionJianqing Fan, Tao Huang, Runze Li
Journal of the American Statistical Association|December 25, 2012
Vast Volatility Matrix Estimation using High Frequency Data for Portfolio SelectionJianqing Fan, Yingying Li, Ke Yu
Journal of the American Statistical Association|April 15, 2014
Estimating False Discovery Proportion Under Arbitrary Covariance DependenceJianqing Fan, Xu Han, Weijie Gu
Journal of the American Statistical Association|September 13, 2024
Are Latent Factor Regression and Sparse Regression Adequate?Jianqing Fan, Zhipeng Lou, Mengxin Yu
Pageof 13

Showing results (21-30 of 123) with videos related to

Sort By:
Pageof 13
Stochastic Processes and Their Applications|June 27, 2022
Adaptive Huber Regression on Markov-dependent DataJianqing Fan, Yongyi Guo, Bai Jiang
Annals of Statistics|July 26, 2021
ASYMMETRY HELPS: EIGENVALUE AND EIGENVECTOR ANALYSES OF ASYMMETRICALLY PERTURBED LOW-RANK MATRICESYuxin Chen, Chen Cheng, Jianqing Fan
Journal of Machine Learning Research : JMLR|May 24, 2011
Ultrahigh dimensional feature selection: beyond the linear modelJianqing Fan, Richard Samworth, Yichao Wu
Journal of the Royal Statistical Society. Series B, Statistical Methodology|May 19, 2011
Penalized Composite Quasi-Likelihood for Ultrahigh-Dimensional Variable SelectionJelena Bradic, Jianqing Fan, Weiwei Wang
Journal of the American Statistical Association|January 27, 2012
Nonparametric Independence Screening in Sparse Ultra-High Dimensional Additive ModelsJianqing Fan, Yang Feng, Rui Song
Annals of Statistics|June 5, 2012
HIGH DIMENSIONAL COVARIANCE MATRIX ESTIMATION IN APPROXIMATE FACTOR MODELSJianqing Fan, Yuan Liao, Martina Mincheva
Journal of the American Statistical Association|August 27, 2009
Analysis of Longitudinal Data with Semiparametric Estimation of Covariance FunctionJianqing Fan, Tao Huang, Runze Li
Journal of the American Statistical Association|December 25, 2012
Vast Volatility Matrix Estimation using High Frequency Data for Portfolio SelectionJianqing Fan, Yingying Li, Ke Yu
Journal of the American Statistical Association|April 15, 2014
Estimating False Discovery Proportion Under Arbitrary Covariance DependenceJianqing Fan, Xu Han, Weijie Gu
Journal of the American Statistical Association|September 13, 2024
Are Latent Factor Regression and Sparse Regression Adequate?Jianqing Fan, Zhipeng Lou, Mengxin Yu
Pageof 13