Jinchi Lv  
 
 

Publications [Software] [Citations 1 | 2]

2017
Kong, Y., Li, D., Fan, Y. and Lv, J. (2017).
Interaction pursuit in high-dimensional multi-response regression via distance correlation.
The Annals of Statistics 45, 897-922. [PDF] [Supplementary Material] [Technical Report] [Software]


Demirkaya, E. and Lv, J. (2017).
Discussion of "Random-projection ensemble classification."
Journal of the Royal Statistical Society Series B 79, 1008-1009. [PDF]

Lu, Y., Lv, J., Fuhrman, J. A. and Sun, F. (2017).
Towards enhanced and interpretable clustering/classification in integrative genomics.
Nucleic Acids Research, to appear. [PDF]

Fan, J. and Lv, J. (2017).
Sure independence screening (invited review article).
Wiley StatsRef: Statistics Reference Online, to appear. [PDF]

Fan, Y., Demirkaya, E., Li, G. and Lv, J. (2017).
RANK: large-scale inference with graphical nonlinear knockoffs.
Manuscript
. [PDF] [Technical Report] [Software]

Fan, Y., Demirkaya, E. and Lv, J. (2017).
Nonuniformity of p-values can occur early in diverging dimensions.
Manuscript
. [PDF] [Technical Report]

Candès, E. J., Fan, Y., Janson, L. and Lv, J. (2017).
Panning for gold: Model-free knockoffs for high-dimensional controlled variable selection.
Manuscript
. [PDF] [Technical Report] [Software]

Ren, Z., Kang, Y., Fan, Y. and Lv, J. (2017).
Tuning-free heterogeneity pursuit in massive networks.
Manuscript
. [PDF] [Technical Report] [Software]

Fan, Y., Kong, Y., Li, D. and Lv, J. (2017).
Interaction pursuit with feature screening and selection.
Manuscript
. [PDF] [Technical Report] [Software]

Uematsu, Y., Fan, Y., Chen, K., Lv, J. and Lin, W. (2017).
SOFAR: large-scale association network learning.
Manuscript. [PDF] [Technical Report] [Software]


Zheng, Z., Bahadori, M. T., Liu, Y. and Lv, J. (2017).
Scalable interpretable multi-response regression via SEED.
Manuscript. [PDF] [Technical Report] [Software]


Zheng, Z., Lv, J. and Lin, W. (2017).
Nonsparse learning with latent variables.
Manuscript. [PDF] [Technical Report] [Software]


Demirkaya, E., Feng, Y., Basu, P. and Lv, J. (2017).
Large-scale model selection with misspecification.
Manuscript. [PDF] [Technical Report] [Software]


2016
Fan, Y. and Lv, J. (2016).
Innovated scalable efficient estimation in ultra-large Gaussian graphical models.
The Annals of Statistics 44, 2098-2126. [PDF] [Supplementary Material] [Technical Report] [Software]

Kong, Y., Zheng, Z. and Lv, J. (2016).
The constrained Dantzig selector with enhanced consistency.
Journal of Machine Learning Research 17, 1-22. [PDF] [Technical Report] [Software]

Zhang, H., Zheng, Y., Zhang, Z., Gao, T., Joyce, B., Yoon, G., Zhang, W., Schwartz, J., Just, A., Colicino, E., Vokonas, P., Zhao, L., Lv, J., Baccarelli, A., Hou, L. and Liu, L. (2016).
Estimating and testing high-dimensional mediation effects in epigenetic studies.
Bioinformatics 32, 3150-3154. [PDF]

2015
Kim, S., Ogawa, K., Lv, J., Schweighofer, N. and Imamizu, H. (2015).
Neural substrates related to motor memory with multiple timescales in sensorimotor adaptation.
PLOS Biology 13, e1002312. [PDF]

 
2014
Lv, J. and Liu, J. S. (2014).
Model selection principles in misspecified models.
Journal of the Royal Statistical Society Series B 76, 141-167. [PDF] [Technical Report]

Fan, Y. and Lv, J. (2014).
Asymptotic properties for combined L1 and concave regularization.
Biometrika 101, 57-70. [PDF] [Technical Report] [Software]

Zheng, Z., Fan, Y. and Lv, J. (2014).
High dimensional thresholded regression and shrinkage effect.
Journal of the Royal Statistical Society Series B 76, 627-649. [PDF] [Technical Report] [Software]

Lv, J. and Zheng, Z. (2014).
Discussion: A significance test for the Lasso.
The Annals of Statistics 42, 493-500. [PDF]
 
2013
Lv, J. (2013).
Impacts of high dimensionality in finite samples.
The Annals of Statistics 41, 2236-2262. [PDF]

Fan, Y. and Lv, J. (2013).
Asymptotic equivalence of regularization methods in thresholded parameter space.
Journal of the American Statistical Association 108, 1044-1061. [PDF] [Technical Report] [Software]

Lin, W. and Lv, J. (2013).
High-dimensional sparse additive hazards regression.
Journal of the American Statistical Association 108, 247-264. [PDF] [Technical Report] [Software]
 
2011
Fan, J. and Lv, J. (2011).
Nonconcave penalized likelihood with NP-dimensionality.
IEEE Transactions on Information Theory 57, 5467-5484. [PDF] [Technical Report] [Software]

Fan, J., Lv, J. and Qi, L. (2011).
Sparse high-dimensional models in economics (invited review article).
Annual Review of Economics 3, 291-317. [PDF] [Technical Report]
 
2010
Fan, J. and Lv, J. (2010).
A selective overview of variable selection in high dimensional feature space (invited review article).
Statistica Sinica 20, 101-148. [PDF]

Fan, J. and Lv, J. (2010).
Comments on: L1-penalization for mixture regression models.
TEST 19, 264-269. [PDF]
 
2009
Lv, J. and Fan, Y. (2009).
A unified approach to model selection and sparse recovery using regularized least squares.
The Annals of Statistics 37, 3498-3528. [PDF] [Software]

James, G., Radchenko, P. and Lv, J. (2009).
DASSO: connections between the Dantzig selector and Lasso.
Journal of the Royal Statistical Society Series B 71, 127-142. [PDF]
 
2008
Fan, J. and Lv, J. (2008).
Sure independence screening for ultrahigh dimensional feature space (with discussion).
Journal of the Royal Statistical Society Series B 70, 849-911. [PDF] [Addendum]

Fan, J. and Lv, J. (2008).
Rejoinder: Sure independence screening for ultrahigh dimensional feature space.
Journal of the Royal Statistical Society Series B 70, 905-908. [PDF]

Fan, J., Fan, Y. and Lv, J. (2008).
High dimensional covariance matrix estimation using a factor model.
Journal of Econometrics 147, 186-197. [PDF] [Technical Report]
 
2007
Cai, T. and Lv, J. (2007).
Discussion: The Dantzig selector: statistical estimation when p is much larger than n.
The Annals of Statistics 35, 2365-2369. [PDF]

Fan, J., Fan, Y. and Lv, J. (2007).
Aggregation of nonparametric estimators for volatility matrix.
Journal of Financial Econometrics 5, 321-357. [PDF]

Lv, J. (2007).
High dimensional variable selection and covariance matrix estimation.
Ph.D. Dissertation, Department of Mathematics, Princeton University.