References
- Fryer MJ. A review of some non-parametric methods of density estimation. J Inst Maths Appl. 1977;20:335–354. doi: 10.1093/imamat/20.3.335
- Silverman BW. Density estimation for statistics and data analysis. London: Chapman & Hall; 1986.
- Wand MP, Jones MC. Kernel smoothing. London: Chapman & Hall; 1995.
- Stefanski L, Carroll R. Deconvoluting kernel density estimators. Statistics. 1990;21:169–184. doi: 10.1080/02331889008802238
- Fan J. Deconvolution with supersmooth distributions. Can J Stat. 1992;20:155–169. doi: 10.2307/3315465
- Abramowitz M, Stegun I. Handbook of mathematical functions. New York: Dover; 1965.
- Weideman JAC. Computation of the complex error function. SIAM J Numer Anal. 1994;31:1497–1518. doi: 10.1137/0731077
- Poppe GPM, Wijers CMJ. More efficient computation of the complex error function. ACM TransMathSoftw. 1990;16:38–46.
- Zaghloul MR, Ali AN. Algorithm 916: Computing the Faddeyeva and Voigt functions. ACM TransMathSoftw. 2012;38:15:1–15: 22.
- Sheather SJ, Jones MC. A reliable data-based bandwidth selection method for kernel density estimation. J Roy Stat Soc B. 1991;53:683–690.
- Loader CR. Bandwidth selection: Classical or plug-in? Ann Stat. 1999;27:415–438.
- Chacón J, Tenreiro C. Exact and asymptotically optimal bandwidths for kernel estimation of density functionals. Methodol Comput Appl Probab. 2012;14:523–548. doi: 10.1007/s11009-011-9243-x
- Hesse CH. Data-driven deconvolution. J Nonparametr Stat. 1999;10:343–373. doi: 10.1080/10485259908832766
- Delaigle A, Gijbels I. Practical bandwidth selection in deconvolution kernel density estimation. Comput Stat Data Anal. 2004;45:249–267. doi: 10.1016/S0167-9473(02)00329-8
- Wang XF, Ye D. The effects of error magnitude and bandwidth selection for deconvolution with unknown error distribution. J Nonparametr Stat. 2012;24:153–167. doi: 10.1080/10485252.2011.647024
- Wang XF, Wang B. Deconvolution estimation in measurement error models: The R package decon. J Stat Softw. 2011;39:10.
- Wang XF, Fan Z, Wang B. Estimating smooth distribution function in the presence of heteroscedastic measurement errors. Comput Stat Data Anal. 2010;54:25–36. doi: 10.1016/j.csda.2009.08.012
- Ruiz S. An algebraic identity leading to Wilson's theorem. Math Gaz. 1996;80(489):579–582. doi: 10.2307/3618534
- Spivey MZ. Combinatorial sums and finite differences. Discrete Math. 2007;307:3130–3146. doi: 10.1016/j.disc.2007.03.052
- Goldberg D. What every computer scientist should know about floating-point arithmetic. ACM ComputSurv. 1991;23:5–48. doi: 10.1145/103162.103163