Description Usage Arguments Value See Also Examples
The ASH1D
function performs univariate density estimations based on
the Average Shifted Histogram method implemented in ash1 followed by
a linear interpolation of density values.
1 |
x |
numeric vector. |
data |
numeric vector (optional). |
n |
number of bins. |
k |
smoothing in number of bins. |
r |
optional numeric vector determining the range of values to be considered. |
rx |
range expansion. |
safe |
logical (default = TRUE, yes). |
... |
optional argument ( |
ASH1D
returns a numeric vector with estimated densities.
ASH2D
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | ## Not run:
n1 <- 30000
n2 <- 60000
g <- c(rep(1, n1), rep(2, n2))
x <- c(rnorm(n1, 0, 1), rnorm(n2, 0, 5))
o <- order(x)
x <- x[o]
g <- g[o]
dt <- ASH1D(x, k = 5)
d1 <- ASH1D(x, data = x[g == 1], k = 10)
d2 <- ASH1D(x, data = x[g == 2], k = 10)
clr <- c(
dt = grey(0.0, 0.6),
d1 = rgb(1.0, 0.5, 0.0, 0.6),
d2 = rgb(0.0, 0.5, 1.0, 0.6),
`d1 + d2` = rgb(1.0, 0.0, 0.0, 0.6)
)
EmptyPlot(xlim = range(x), ylim = range(dt, d1, d2, d1 + d2))
par(lwd = 1.5)
lines(x, d1 + d2, col = clr[4])
lines(x, dt, col = clr["dt"])
lines(x, d1, col = clr["d1"])
lines(x, d2, col = clr["d2"])
legend("topright", legend = names(clr), fill = clr, bty = "n")
## End(Not run)
|
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