233
Views
4
CrossRef citations to date
0
Altmetric
Articles

Robust model-free feature screening for ultrahigh dimensional surrogate data

, , , &
Pages 550-569 | Received 22 Mar 2019, Accepted 05 Nov 2019, Published online: 13 Nov 2019

References

  • Ellenberg SS, Hamilton JM. Surrogate endpoints in clinical trials: cancer. Stat Med. 1989;8:405–413. doi: 10.1002/sim.4780080404
  • Alonzo TA, Pepe MS, Lumley T. Estimating disease prevalence in two-phase studies. Biostatistics. 2003;4:313–326. doi: 10.1093/biostatistics/4.2.313
  • Rubin DB, Little RJ. Statistical analysis with missing data. Hoboken, NJ: John Wiley & Sons; 2002.
  • Wang Q, Linton O, Härdle W. Semiparametric regression analysis with missing response at random. J Am Stat Assoc. 2004;99:334–345. doi: 10.1198/016214504000000449
  • Qin J, Shao J, Zhang B. Efficient and doubly robust imputation for covariate-dependent missing responses. J Am Stat Assoc. 2008;103:797–810. doi: 10.1198/016214508000000238
  • Wu C, Ma S. A selective review of robust variable selection with applications in bioinformatics. Brief Bioinformatics. 2015;16(5):873–883. doi: 10.1093/bib/bbu046
  • Fan J, Lv J. Sure independence screening for ultrahigh dimensional feature space. J R Stat Soc B. 2008;70:849–911. doi: 10.1111/j.1467-9868.2008.00674.x
  • Zhu L, Li L, Li R, et al. Model-free feature screening for ultrahigh-dimensional data. J Am Stat Assoc. 2011;106:1464–1475. doi: 10.1198/jasa.2011.tm10563
  • Li G, Peng H, Zhang J et al. Robust rank correlation based screening. Ann Stat. 2012;40:1846–1877. doi: 10.1214/12-AOS1024
  • Li R, Zhong W, Zhu L. Feature screening via distance correlation learning. J Am Stat Assoc. 2012;107:1129–1139. doi: 10.1080/01621459.2012.695654
  • Song R, Lu W, Ma S, et al. Censored rank independence screening for high-dimensional survival data. Biometrika. 2014;101(4):799–814. doi: 10.1093/biomet/asu047
  • Zhou T, Zhu L. Model-free feature screening for ultrahigh dimensional censored regression. Stat Comput. 2017;27(4):947–961. doi: 10.1007/s11222-016-9664-z
  • Cui H, Li R, Zhong W. Model-free feature screening for ultrahigh dimensional discriminant analysis. J Am Stat Assoc. 2015;110:630–641. doi: 10.1080/01621459.2014.920256
  • Lai P, Song F, Chen K, et al. Model free feature screening with dependent variable in ultrahigh dimensional binary classification. Stat Probab Lett. 2017;125:141–148. doi: 10.1016/j.spl.2017.02.011
  • Wu Y, Yin G. Conditional quantile screening in ultrahigh-dimensional heterogeneous data. Biometrika. 2015;102(1):65–76. doi: 10.1093/biomet/asu068
  • Zhang J, Liu Y, Wu Y. Correlation rank screening for ultrahigh-dimensional survival data. Comput Stat Data Anal. 2017;108:121–132. doi: 10.1016/j.csda.2016.11.005
  • Lai P, Liu Y, Liu Z, et al. Model free feature screening for ultrahigh dimensional data with responses missing at random. Comput Stat Data Anal. 2017;105:201–216. doi: 10.1016/j.csda.2016.08.008
  • Ma S. Multiple augmentation with partial missing regressors. Biom J. 2006;48(1):83–92. doi: 10.1002/bimj.200510168
  • Tsiatis A. Semiparametric theory and missing data. Berlin: Springer Verlag; 2006.
  • Lai P, Wang Q. Semiparametric efficient estimation for partially linear single-index models with responses missing at random. J Multivar Anal. 2014;128(14):33–50. doi: 10.1016/j.jmva.2014.03.001
  • Masry E. Multivariate local polynomial regression for time series: uniform strong consistency and rates. J Time Ser Anal. 1996;17:571–599. doi: 10.1111/j.1467-9892.1996.tb00294.x
  • Wang Q, Yin X. A nonlinear multi-dimensional variable selection method for high dimensional data: sparse mave. Comput Stat Data Anal. 2008;52(9):4512–4520. doi: 10.1016/j.csda.2008.03.003
  • Serfling R. Approximation theorems of mathematical and statistics. New York: John Wiley & Sons, Inc.; 1980.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.