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Kernel Functions

Kernel functions are used for smoothing histograms. The following R code displays the use of four popular kernel choices (Gaussian, triangular, tricube, and uniform):

x_grid = seq(-3, 3, length.out = 100)
gaussian = function(x) dnorm(x)
triangular = function(x) {
ind = abs(x) > 1
x = 1 - abs(x)
x[ind] = 0
return(x)
}
tricube = function(x) {
ind = abs(x) > 1
x = (1 - abs(x)^3)^3
x[ind] = 0
return(x)
}
uniform = function(x) {
ind = abs(x) > 1
x = x * 0 + 1/2
x[ind] = 0
return(x)
}
df = stack(list("uniform" = uniform(x_grid),
"triangular" = triangular(x_grid),
"gaussian" = gaussian(x_grid),
"tricube" = tricube(x_grid),
"uniform" = uniform(x_grid / 2) / 2,
"triangular" = triangular(x_grid / 2) / 2,
"gaussian" = gaussian(x_grid / 2) / 2,
"tricube" = tricube(x_grid / 2) / 2))
head(df) # first six lines
names(df) = c("kernel.value", "kernel.type")
df$x = x_grid
df$h[1:400] = "$h = 1$"
df$h[401:800] = "$h = 2$"
head(df) # first six lines
qplot(x,
kernel.value,
data = df,
facets = kernel.type~h,
geom = "line",
xlab = "$x$",
ylab = "$K_h(x)$")
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