Free Access
Issue
ESAIM: PS
Volume 20, 2016
Page(s) 1 - 17
DOI https://doi.org/10.1051/ps/2015018
Published online 03 June 2016
  1. P.K. Bhattacharya and P.L. Zhao, Semiparametric inference in a partial linear model. Ann. Statist. 25 (1997) 244–262. [CrossRef] [MathSciNet] [Google Scholar]
  2. R.J. Carroll, J. Fan, I. Gijbels and M.P. Wand, Generalized partially linear single-index models. J. Amer. Statist. Assoc. 92 (1997) 477–489. [CrossRef] [MathSciNet] [Google Scholar]
  3. H. Chen, Convergence rates for parametric components in a partly linear model. Ann. Statist. 16 (1988) 136–141. [CrossRef] [MathSciNet] [Google Scholar]
  4. C.H. Chen and K.C. Li Can, SIR be as popular as multiple linear regression. Statist. Sinica 8 (1998) 289–316. [MathSciNet] [Google Scholar]
  5. F. Chiaromonte, R.D. Cook and B. Li, Sufficient Dimension Reduction in Regressions With Categorical Predictors. Ann. Statist. 30 (2002) 475–497. [CrossRef] [MathSciNet] [Google Scholar]
  6. R.D. Cook and S. Weisberg, Discussion of “Sliced inverse regression for dimension reduction” by K.C.Li. J. Amer. Statist. Assoc. 86 (1991) 328–332. [Google Scholar]
  7. P. Diaconis and D. Freedman, Asymptotics of graphical projection pursuit. Ann. Statist. 12 (1984) 793–815. [Google Scholar]
  8. X. Ding, X.H. Zhou and Q. Wang, A partially linear single-index transformation model and its nonparametric estimation. The Canadian J. Statistics 43 (2015) 97–117. [CrossRef] [Google Scholar]
  9. K. Doksum and J.Y. Koo, On spline estimators and prediction intervals in nonparametric smoothing. Comput. Statist. Data Anal. 35 (2000) 67–82. [CrossRef] [MathSciNet] [Google Scholar]
  10. J. Fan and R. Li Variable selection via nonconcave penalized likelihood and its oracle properties. J. Amer. Statist. Assoc. 96 (2001) 1348–1360. [Google Scholar]
  11. J. Fan, T.C. Hu and Y.K. Truong, Robust Nonparametric Function Estimation. Scand. J. Statist. 21 (1994) 433–446. [MathSciNet] [Google Scholar]
  12. Z. Feng, X.M. Wen, Z. Yu and L. Zhu, On partial sufficient dimension reduction with applications to partially linear multi-index models. J. Amer. Statist. Assoc. 108 (2013) 237–246. [CrossRef] [MathSciNet] [Google Scholar]
  13. F.R. Hampel, E.M. Ronchetti, P.J. Rousseeuw and W.A. Stahel, Robust Statistics: The approach based on influence functions, Wiley Ser. Probab. Stat. Wiley-Interscience (2005). [Google Scholar]
  14. W. Härdle, Partially Linear Models. Springer, New York (2000). [Google Scholar]
  15. D. Harrison and D. Rubinfeld, Hedonic housing pries and the demand for clean air. J. Environ. Econ. Manage. 5 (1978) 81–102. [CrossRef] [Google Scholar]
  16. T. Hastie and R. Tibshirani, Generalized additive models. Chapman & Hall, London (1990) [Google Scholar]
  17. X. He and B. Shi, Bivariate tensor-product B-splines in a partially linear regression. J. Multivariate Anal. 58 (1996) 162–181. [CrossRef] [MathSciNet] [Google Scholar]
  18. N. Heckman, Spline smoothing in a partly linear model. J. Roy. Statist. Soc. Ser. A 48 (1986) 244–248. [Google Scholar]
  19. D.R. Hunter and K. Lange, quantile regression via an MM algorithm. J. Comp. Graph. Statist. 9 (2000) 60–77. [Google Scholar]
  20. R. Jiang, Z.G. Zhou, W.M. Qian and W.Q. Shao, Single-index composite quantile regression. J. Korean Statist. Soc. 41 (2012) 323–332. [CrossRef] [MathSciNet] [Google Scholar]
  21. K. Knight, Limiting distributions for L1 regression estimators under general conditions. Ann. Statist. 26 (1998) 755–770. [CrossRef] [MathSciNet] [Google Scholar]
  22. R. Koenker, Quantile regression. Cambridge Univ. Press, Cambridge (2005) [Google Scholar]
  23. R. Koenker and G. Bassett, Regression quantiles. Econometrica 46 (1978) 33–50. [Google Scholar]
  24. S. Lee, Efficient semiparametric estimation of a partially linear quantile regression model. Econ. Theory 19 (2003) 1–31. [Google Scholar]
  25. T.C.M. Lee and H. Oh, Robust penalized regression spline fitting with application to additive mixed modeling. Comput. Statist. 22 (2007) 159–171. [CrossRef] [MathSciNet] [Google Scholar]
  26. K.C. Li, Sliced inverse regression for dimension reduction. J. Amer. Statist. Assoc. 102 (1991) 997–1008. [Google Scholar]
  27. B. Li and S. Wang, On directional regression for dimension reduction. J. Amer. Statist. Assoc. 33 (2007) 1580–1616. [Google Scholar]
  28. L. Li, and X. Yin, Sliced inverse regression with regularizations. Biometrics. 64 (2008) 124–131. [CrossRef] [MathSciNet] [PubMed] [Google Scholar]
  29. Y. Li and L.X. Zhu, Asymptotics for sliced average variance estimation. Ann. Statist. 35 (2007) 41–69. [CrossRef] [MathSciNet] [Google Scholar]
  30. X. Liu, L. Wang and H. Liang, Estimation and variable selection for semiparametric additive partial linear models. Statist. Sinica 21 (2011) 1225–1248. [CrossRef] [MathSciNet] [Google Scholar]
  31. D. Pollard, Asymptotics for least absolute deviation regression estimators. Econ. Theory 7 (1991) 186–199. [CrossRef] [Google Scholar]
  32. Y. Sun, Semiparametric efficient estimation of partially linear quantile regression models. Ann. Econ. Finance 6 (2005) 105–127. [Google Scholar]
  33. R. Tibshirani, Regression shrinkage and selection via the lasso. J. Roy. Statist. Soc. Ser. B 58 (1996) 267–288. [Google Scholar]
  34. D. Tyler, Asymptotic inference for eigenvectors. Ann. Statist. 9 (1981) 725–736. [CrossRef] [MathSciNet] [Google Scholar]
  35. J.L. Wang L. Xue, L. Zhu and Y.S. Xhong, Estimation for a partial-linear single-index model. Ann. Statist. 38 (2010) 246–274. [MathSciNet] [Google Scholar]
  36. S.N. Wood, Thin plate regression splines. J. R. Statist. Soc. B. 65 (2003) 95–114. [Google Scholar]
  37. Y. Xia and W. Härdle, Semi-parametric estimation of partially linear single-index models. J. Multivariate Anal. 97 (2006) 1162–1184. [CrossRef] [MathSciNet] [Google Scholar]
  38. Y. Xia, H. Tong, W.K. Li and L.X. Zhu, An adaptive estimation of dimension reduction space. J. Roy. Statist. Soc. Ser. B. 64 (2002) 363–410. [CrossRef] [Google Scholar]
  39. Y. Yu and D. Ruppert, Penalized spline estimation for partially linear single-index models. J. Amer. Statist. Assoc. 97 (2002) 1042–1054. [CrossRef] [MathSciNet] [Google Scholar]
  40. L.P. Zhu, R. Li and H. Cui, Robust estimation for partially linear models with large-dimensional covariates. Science China Mathematics. 56 (2013) 2069–2088. [CrossRef] [MathSciNet] [PubMed] [Google Scholar]
  41. L.X. Zhu, B.Q. Miao and H. Peng, Sliced inverse regression with large dimensional covariates. J. Amer. Statist. Assoc. 101 (2006) 630–643. [CrossRef] [MathSciNet] [Google Scholar]
  42. H. Zou and M. Yuan, Composite quantile regression and the oracle model selection theory. Ann. Statist. 36 (2008) 1108–1126. [CrossRef] [MathSciNet] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.