2009 - Fellow of John Simon Guggenheim Memorial Foundation
2005 - Fellow of the American Association for the Advancement of Science (AAAS)
2000 - COPSS Presidents' Award
1999 - Fellow of the American Statistical Association (ASA)
His main research concerns Applied mathematics, Statistics, Estimator, Nonparametric regression and Mathematical optimization. His Applied mathematics research is multidisciplinary, relying on both Regression analysis, Linear regression, Polynomial regression and Polynomial. His research in Estimator intersects with topics in Quantile, Kernel method and Conditional probability distribution.
The various areas that Jianqing Fan examines in his Nonparametric regression study include Generalized linear model, M-estimator and Local regression. His work carried out in the field of Mathematical optimization brings together such families of science as Smoothing and Lasso. His Penalty method research is multidisciplinary, incorporating perspectives in Likelihood function, Feature selection and Model selection.
Jianqing Fan mostly deals with Applied mathematics, Estimator, Statistics, Econometrics and Nonparametric statistics. The concepts of his Applied mathematics study are interwoven with issues in Linear regression, Covariance, Linear model, Covariance matrix and Mathematical optimization. Jianqing Fan has included themes like Smoothing and Polynomial regression in his Mathematical optimization study.
His Estimator research integrates issues from Algorithm, Sample size determination and Minimax. His work on Volatility and Factor analysis is typically connected to Estimation as part of general Econometrics study, connecting several disciplines of science. Jianqing Fan studies Nonparametric regression, a branch of Nonparametric statistics.
Jianqing Fan mainly focuses on Applied mathematics, Estimator, Factor analysis, Algorithm and Covariance. His Applied mathematics study incorporates themes from Random matrix, Linear regression, Statistical inference, Minimax and Covariance matrix. His Linear regression research is multidisciplinary, incorporating elements of Covariate, Sample size determination, Regression and Lasso.
His work in the fields of Estimation of covariance matrices and Robust statistics overlaps with other areas such as Thresholding and Initialization. His Factor analysis research incorporates elements of Principal component analysis, Inference and Artificial intelligence. His biological study spans a wide range of topics, including Statistical hypothesis testing, Regression analysis and Model selection.
Applied mathematics, Estimator, Matrix completion, Algorithm and Random matrix are his primary areas of study. His Applied mathematics research includes themes of Covariate, Covariance matrix, Upper and lower bounds, Symmetric matrix and Factor analysis. In the subject of general Covariance matrix, his work in Estimation of covariance matrices is often linked to Thresholding, thereby combining diverse domains of study.
His study in Algorithm is interdisciplinary in nature, drawing from both Statistical inference, Null hypothesis and Covariance. His Principal component analysis research focuses on Random projection and how it connects with Statistical model. He has researched Bounded function in several fields, including Critical point, Condition number and Mathematical optimization.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
Jianqing Fan;Runze Li.
Journal of the American Statistical Association (2001)
Local Polynomial Modelling and Its Applications: Monographs on Statistics and Applied Probability 66
J. Fan;I. Gijbels.
Local polynomial modelling and its applications
Jianqing Fan;Irène Gijbels.
Nonlinear Time Series: Nonparametric and Parametric Methods
Jianqing Fan;Qiwei Yao.
Sure independence screening for ultrahigh dimensional feature space
Jianqing Fan;Jinchi Lv.
Journal of The Royal Statistical Society Series B-statistical Methodology (2008)
Design-adaptive Nonparametric Regression
Journal of the American Statistical Association (1992)
Local Polynomial Modeling and Its Applications
Hans-Georg Muller;J. Fan;I. Gijbels.
Journal of the American Statistical Association (1998)
Local Linear Regression Smoothers and Their Minimax Efficiencies
Annals of Statistics (1993)
Challenges of Big Data analysis
Jianqing Fan;Fang Han;Han Liu.
National Science Review (2014)
On the Optimal Rates of Convergence for Nonparametric Deconvolution Problems
Annals of Statistics (1991)
Profile was last updated on December 6th, 2021.
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