References
- Belsley, D., Kuh, E., and Welsch, R. (1980), Regression Diagnostics; Identifying Influential Data and Sources of Collinearity, New York, New York: Wiley.
- Chaudhuri, P., Doksum, K., and Samarov, A. (1997), ‘On Average Derivative Quantile Regression’, The Annals of Statistics, 25(2), 715–744.
- Cleveland, W.S. (1979), ‘Robust Locally Weighted Regression and Smoothing Scatterplots’, Journal of the American Statistical Association, 74(368), 829–836.
- Gilley, O.W., and Pace, R.K. (1996), ‘On the Harrison and Rubinfeld Data’, Journal of Environmental Economics and Management, 31(3), 403–405.
- Hall, P., Li, Q., and Racine, J.S. (2007), ‘Nonparametric Estimation of Regression Functions in the Presence of Irrelevant Regressors’, Review of Economics and Statistics, 89(4), 784–789.
- Härdle, W.K., and Gasser, T. (1984), ‘Robust Non-parametric Function Fitting’, Journal of the Royal Statistical Society. Series B, 46, 42–51.
- Hardle, W., and Marron, J.S. (1985), ‘Optimal Bandwidth Selection in Nonparametric Regression Function Estimation’, The Annals of Statistics, 13(4), 1465–1481.
- Harrison, D., and Rubinfeld, D.L. (1978), ‘Hedonic Housing Prices and the Demand for Clean Air’, Journal of Environmental Economics and Management, 5(1), 81–102.
- Henderson, D.J., and Parmeter, C.F. (2015), Applied Nonparametric Econometrics, Cambridge University Press.
- Huber, P.J. (1964), ‘Robust Estimation of a Location Parameter’, The Annals of Mathematical Statistics, 35(1), 73–101.
- Jones, M.C., Marron, J.S., and Sheather, S.J. (1996), ‘A Brief Survey of Bandwidth Selection for Density Estimation’, Journal of the American Statistical Association, 91(433), 401–407.
- Krasker, W.S., Kuh, E., and Welsch, R.E. (1983), ‘Estimation for Dirty Data and Flawed Models’, in Handbook of Econometrics (Vol. 1), eds. Z. Griliches and M. D. Intriligator, Amsterdam: North-Holland, pp. 651–698.
- Leung, D.H.-Y. (2005), ‘Cross-validation in Nonparametric Regression with Outliers’, The Annals of Statistics, 33(5), 2291–2310.
- Leung, D.H. -Y., Marriott, F.H.C., and Wu, E.K.H. (1993), ‘Bandwidth Selection in Robust Smoothing’, Journal of Nonparametric Statistics, 2, 333–339.
- Li, Q., and Racine, J. (2007), Nonparametric Econometrics: Theory and Practice, Princeton, New Jersey: Princeton University Press.
- Li, Q., and Racine, J.S. (2008), ‘Nonparametric Estimation of Conditional Cdf and Quantile Functions with Mixed Categorical and Continuous Data’, Journal of Business & Economic Statistics, 26(4), 423–434.
- Loader, C.R. (1999), ‘Bandwidth Selection: Classical Or Plug-in?’, The Annals of Statistics, 27(2), 415–438.
- Pollard, D. (1991), ‘Asymptotics for Least Absolute Deviation Regression Estimators’, Econometric Theory, 7, 186–199.
- Racine, J. (2008), ‘Nonparametric Econometrics: A Primer’, Foundations and Trends(R) in Econometrics, 3(1), 1–88.
- Rice, J. (1984), ‘Bandwidth Choice for Nonparametric Regression’, The Annals of Statistics, 12(4), 1215–1230.
- Venables, W.N., and Ripley, B.D. (2002), Modern Applied Statistics with S, (4th ed.), New York: Springer.
- Wang, S., Li, A., Wen, K., and Wu, X. (2020), ‘Robust Kernels for Kernel Density Estimation’, Economics Letters, 191, 109138.
- Wang, T.F., and Scott, D.W. (1994), ‘The l1 Method for Robust Nonparametric Regression’, Journal of the American Statistical Association, 89(425), 65–76.
- Watson, G. (1964), ‘Smooth Regression Analysis’, Sankhyā Sers, A 26, 359–372.
- Whittle, P. (1960), ‘Bounds for the Moments of Linear and Quadratic Forms in Independent Variables’, Teor. Verojatnost. i Primenen., 5, 331–335.
![Supercharge Your Next Research Paper: Research and write your next paper with Jenni AI.]({"type":"image" , "src" : "/sda/112440/MPU-Jenni-AI-ECONOMICS.png"})