| kef {Conake} | R Documentation |
Continuous associated kernel function
Description
This function computes the discrete associated kernel function; see Chen (1999) and also Chen (2000).
Usage
kef(x, t, h, ker, a = 0, b = 1)
Arguments
x |
The target. |
t |
A single value or the grid where the continuous associated kernel function is computed. |
h |
The bandwidth or smoothing parameter. |
ker |
The associated kernel: "BE" extended beta, "GA" gamma, "LN" lognormal and "RIG" reciprocal inverse Gaussian. |
a |
The left bound of the support used for extended beta kernel. Default value is 0 for beta kernel. |
b |
The right bound of the support used for extended beta kernel. Default value is 1 for beta kernel. |
Details
The associated kernel is one of the four which have been defined in the sections above : extended beta, gamma, lognormal and reciprocal inverse Gaussian; see Igarashi and Kakizawa (2015) and also Libengué (2013).
Value
Returns the value of the discrete associated kernel function at t according to the target and the bandwidth.
Author(s)
W. E. Wansouwé, F.G. Libengué and C. C. Kokonendji
References
Chen, S. X. (1999). Beta kernels estimators for density functions, Computational Statistics and Data Analysis 31, 131 - 145.
Chen, S. X. (2000). Gamma kernels estimators for density functions, Annals of the Institute of Statistical Mathematics 52, 471 - 480.
Libengué, F.G. (2013).Méthode Non-Paramétrique par Noyaux Associés Mixtes et Applications, Ph.D. Thesis Manuscript (in French) to Université de Franche-Comté, Besançon, France and Université de Ouagadougou, Burkina Faso, June 2013, LMB no. 14334, Besançon.
Igarashi, G. and Kakizawa, Y. (2015). Bias correction for some asymmetric kernel estimators, Journal of Statistical Planning and Inference 159, 37 - 63.
Examples
x<-4
h<-0.1
t<-0:10
kef(x,t,h,"GA")