Nonparametric Kernel Methods for Qualitative and Quantitative Data

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Chapman and Hall/CRC

Reference1 articles.

1. 3, of Empirical Li, Q., and J. S. Racine. 2004. Cross-validated local linear nonparametric regression. Statistica Sinica 14(2): 485–512. Li, Q., and J. S. Racine. 2007. Nonparametric Econometrics: Theory and Practice. Princeton, NJ: Princeton University Press. Li, Q., and J. S. Racine. 2008. Nonparametric estimation of conditional CDF and quantile functions with mixed categorical and continuous data. Journal of Business and Economic Statistics. 26(4): 423–434. Lindley, D. V., and A. F. M. Smith. 1972. Bayes estimates for the linear model. Journal of the Royal Statistical Society 34: 1–41. Nadaraya, E. A. 1965. On nonparametric estimates of density functions and regression curves. Theory of Applied Probability 10: 186–190. Ouyang, D., Q. Li, and J. S. Racine. 2006. Cross-validation and the estimation of probability distributions with categorical data. Journal of Nonparametric Statistics 18(1): 69–100. Ouyang, D., Q. Li, and J. S. Racine. 2008. Nonparametric estimation of regression functions with discrete regressors. Econometric Theory. 25(1): 1–42. R Development Core Team. 2008. R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0. http://www.R-project.org Racine, J. S. and Q. Li. 2004. Nonparametric estimation of regression functions with both categorical and continuous data. Journal of Econometrics 119(1): 99–130. Simonoff, J. S. 1996. Smoothing Methods in Statistics. New York: Springer Series in Statistics. Wand, M., and B. Ripley, 2008. KernSmooth: Functions for Kernel Smoothing. R package version 2.22-22. http://CRAN.R-project.org/package= KernSmooth Wang, M. C., and J. van Ryzin, 1981. A class of smooth estimators for discrete distributions. Biometrika 68: 301–309. Watson, G. S. 1964. Smooth regression analysis. Sankhya 26:(15): 359–372. Wooldridge, J. M. 2002. Econometric Analysis of Cross Section and Panel Data. Cambridge, MA: MIT Press.

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