https://orcid.org/0009-0002-4735-8213
References
- Bajari, P., Kahn, M. E. ( 2005). Estimating housing demand with an application to explaining racial segregation in cities. Journal of Business & Economic Statistics 23(1):20–33. doi:10.1198/073500104000000334.
- Cai, Z., Fan, J., Yao, Q. ( 2000). Functional-coefficient regression models for nonlinear time series. Journal of the American Statistical Association 95(451):941–956. doi:10.1080/01621459.2000.10474284.
- Carroll, R. J., Fan, J., Gijbels, I., Wand, M. P. ( 1997). Generalized partially linear single-index models. Journal of the American Statistical Association 92(438):477–489. doi:10.1080/01621459.1997.10474001.
- Chiappori, P.-A., Gandhi, A., Salanié, B., Salanié, F. ( 2009). Identifying preferences under risk from discrete choices. American Economic Review 99(2):356–362. doi:10.1257/aer.99.2.356.
- Fan, J., Irene, G. ( 1996). Local polynomial modelling and its applications. In Monographs on Statistics and Applied Probability. New York: Chapman & Hall/CRC.
- Gasser, T., Kneip, A., Köhler, W. ( 1991). A flexible and fast method for automatic smoothing. Journal of the American Statistical Association 86(415):643–652. doi:10.1080/01621459.1991.10475090.
- Hall, P., Li, QI., Racine, J. S. ( 2007). Nonparametric estimation of regression functions in the presence of irrelevant regressors. Review of Economics and Statistics 89(4):784–789. doi:10.1162/rest.89.4.784.
- Hall, P., Racine, J., Li, QI. ( 2004). Cross-validation and the estimation of conditional probability densities. Journal of the American Statistical Association 99(468):1015–1026. doi:10.1198/016214504000000548.
- Hardle, W., Hall, P., Ichimura, H. ( 1993). Optimal smoothing in single-index models. The Annals of Statistics 21(1):157–178.
- Hardle, W., Marron, J. S. ( 1985). Optimal bandwidth selection in nonparametric regression function estimation. The Annals of Statistics 13(4):1465–1481.
- Heckman, J. J., Matzkin, R. L., Nesheim, L. ( 2010). Nonparametric identification and estimation of nonadditive hedonic models. Econometrica 78(5):1569–1591.
- Henderson, D. J., Li, QI., Parmeter, C. F., Yao, S. ( 2015). Gradient-based smoothing parameter selection for nonparametric regression estimation. Journal of Econometrics 184(2):233–241. doi:10.1016/j.jeconom.2014.09.007.
- Jones, M. C., Marron, J. S., Sheather, S. J. ( 1996). A brief survey of bandwidth selection for density estimation. Journal of the American Statistical Association 91(433):401–407. doi:10.1080/01621459.1996.10476701.
- Li, D., Li, Q. ( 2010). Nonparametric/semiparametric estimation and testing of econometric models with data dependent smoothing parameters. Journal of Econometrics 157(1):179–190. doi:10.1016/j.jeconom.2009.10.026.
- Li, Q., Racine, J. ( 2004). Cross-validated local linear nonparametric regression. Statistica Sinica 14(2):485–512.
- Martins, M. F. O. ( 2001). Parametric and semiparametric estimation of sample selection models: An empirical application to the female labour force in Portugal. Journal of Applied Econometrics 16(1):23–39. doi:10.1002/jae.572.
- Ruppert, D., Sheather, S. J., Wand, M. P. ( 1995). An effective bandwidth selector for local least squares regression. Journal of the American Statistical Association 90(432):1257–1270. doi:10.1080/01621459.1995.10476630.
- Xia, Y., Härdle, W. ( 2006). Semi-parametric estimation of partially linear single-index models. Journal of Multivariate Analysis 97(5):1162–1184. doi:10.1016/j.jmva.2005.11.005.