set.seed(12345)
n <- 6; nout <- 300L
x <- sort(runif(n))
xout <- sort(runif(nout, min = x[1], max = x[n]))
y <- sin(2 * pi * x)
cI0 <- interp_ceschino(x = x, xout = xout, y = y)
## compare with a natural spline
require(splines)
spI <- interpSpline(x, y)
spPred0 <- predict(spI, xout)
plot(xout, sin(2 * pi * xout), type = "l", col = "black", lwd = 2,
xlab = "x", ylab = "f(x)", main = "Interpolations")
abline(v = x, col = "gray")
lines(cI0, type = "l", col = "SpringGreen3", lty = 2, lwd = 2)
lines(spPred0, type = "l", col = "SteelBlue2", lty = 3, lwd = 2)
points(x, y, type = "p", pch = 21, col = "red",
bg = "yellow", lwd = 2)
legend("topright", legend = c("true", "Ceschino", "nat. spline"),
col = c("black", "SpringGreen3", "SteelBlue2"),
lty = 1:3, lwd = rep(2, 3))
## derivative estimation
cI1 <- interp_ceschino(x =x, xout = xout, y = y, deriv = 1)
spPred1 <- predict(spI, xout, deriv = 1)
plot(xout, 2 * pi * cos(2 * pi * xout), type = "l", col = "black", lwd = 2,
xlab = "x", ylab = "fprime(x)", main = "Derivatives")
abline(v = x, col = "gray")
lines(cI1, type = "l", col = "SpringGreen3", lty = 2, lwd = 2)
lines(spPred1, type = "l", col = "SteelBlue2", lty = 3, lwd = 2)
points(x, 2 * pi * cos(2 * pi * x), type = "p", pch = 21,
col = "red", bg = "yellow", lwd = 2)
legend("bottomright", legend = c("true", "Ceschino", "nat. spline"),
col = c("black", "SpringGreen3", "SteelBlue2"),
lty = 1:3, lwd = rep(2, 3))
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