Created
April 15, 2016 19:23
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Interpolation and smoothing functions in R
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# Generate data in the form of a sine wave | |
set.seed(1) | |
n <- 1e3 | |
dat <- data.frame( | |
x = 1:n, | |
y = sin(seq(0, 5*pi, length.out = n)) + rnorm(n=n, mean = 0, sd=0.1) | |
) | |
approxData <- data.frame( | |
with(dat, | |
approx(x, y, xout = seq(1, n, by = 10), method = "linear") | |
), | |
method = "approx()" | |
) | |
splineData <- data.frame( | |
with(dat, | |
spline(x, y, xout = seq(1, n, by = 10)) | |
), | |
method = "spline()" | |
) | |
smoothData <- data.frame( | |
x = 1:n, | |
y = as.vector(smooth(dat$y)), | |
method = "smooth()" | |
) | |
loessData <- data.frame( | |
x = 1:n, | |
y = predict(loess(y~x, dat, span = 0.1)), | |
method = "loess()" | |
) | |
library(ggplot2) | |
ggplot(rbind(approxData, splineData, smoothData, loessData), aes(x, y)) + | |
geom_point(dat = dat, aes(x, y), alpha = 0.2, col = "red") + | |
geom_line(col = "blue") + | |
facet_wrap(~method) + | |
ggtitle("Interpolation and smoothing functions in R") + | |
theme_bw(16) |
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