estim_kernel {kernopt} | R Documentation |
Discrete Kernel Density Estimator
Description
Discrete Kernel Density Estimator
Usage
estim_kernel(
kernel = c("optimal", "triang", "epanech", "binomial"),
x,
h,
v,
k = NULL
)
Arguments
kernel |
the type of kernel. Currently supported kernels are limited to: "optimal", "triang", "epanech" and "binomial" |
x |
the list of target points at which the density is calculated |
h |
the bandwidth (or smoothing parameter) |
v |
the vector of observations |
k |
Optional: the integer (positive) parameter that defined the support of the kernel function (corresponds to parameter 'a' for triangular kernel). It is only used for optimal and triangular kernel |
Value
The estimated discrete kernel density values
Examples
n <- 250
mu <- 2 # Mean
x <- 0:10 # target values
y <- sort(rpois(n, mu)) # simulated Poisson observations
# kernel parameters
kernel <- "optimal"
k <- 1
# Cross Validation
H <- seq((max(y) - min(y)) / 200, (max(y) - min(y)) / 2, length.out = 50)
hcv <- cv_bandwidth(kernel = kernel, y, h = H, k = k)
# Kernel estimation
fn_opt_k <- estim_kernel(kernel = kernel, x = x, h = hcv, v = y, k = k)
[Package kernopt version 1.0.0 Index]