Continuous and discrete (count or categorical) estimation of density, probability mass function (p.m.f.) and regression functions are performed using associated kernels. The cross-validation technique and the local Bayesian procedure are also implemented for bandwidth selection.
|Author||W. E. Wansouwé, S. M. Somé and C. C. Kokonendji|
|Date of publication||2015-03-30 00:04:27|
|Maintainer||W. E. Wansouwé <email@example.com>|
|License||GPL (>= 2)|
Ake-package: Associated kernel estimations
dke.fun: Function for density estimation
hbay.fun: Local Bayesian procedure for bandwidth selection
hcvc.fun: Cross-validation function for bandwidth selection for...
hcvd.fun: Cross-validation function for bandwidth selection in p.m.f....
hcvreg.fun: Cross-validation function for bandwidth selection in...
kef: Continuous and discrete associated kernel function
kern.fun: The associated kernel function
kpmfe.fun: Function for associated kernel estimation of p.m.f.
milk: Average daily fat yields.
plot.dke.fun: Plot of density function
plot.hcvc.fun: Plot of cross-validation function for bandwidth selection in...
plot.kern.fun: Plot of associated kernel function
plot.kpmfe.fun: Plot of the function for associated kernel estimation of the...
plot.reg.fun: Plot for associated kernel regression
print.reg.fun: Print for regression function
reg.fun: Function for associated kernel estimation of regression