Finding local maxima and minima

Question

I\'m looking for a computationally efficient way to find local maxima/minima for a large list of numbers in R. Hopefully without for loops...

For exampl

Answer 1

Answer by @42- is great, but I had a use case where I didn't want to use zoo. It's easy to implement this with dplyr using lag and lead:

library(dplyr)
test = data_frame(x = sample(1:10, 20, replace = TRUE))
mutate(test, local.minima = if_else(lag(x) > x & lead(x) > x, TRUE, FALSE)

Like the rollapply solution, you can control the window size and edge cases through the lag/lead arguments n and default, respectively.

Answer 2

Late to the party, but this might be of interest for others. You can nowadays use the (internal) function find_peaks from ggpmisc package. You can parametrize it using threshold, span and strict arguments. Since ggpmisc package is aimed for using with ggplot2 you can directly plot minima and maxima using thestat_peaks and stat_valleys functions:

set.seed(1)
x <- 1:10
y <- runif(10)
# Maxima
x[ggpmisc:::find_peaks(y)]
[1] 4 7
y[ggpmisc:::find_peaks(y)]
[1] 0.9082078 0.9446753
# Minima
x[ggpmisc:::find_peaks(-y)]
[1] 5
y[ggpmisc:::find_peaks(-y)]
[1] 0.2016819    
# Plot
ggplot(data = data.frame(x, y), aes(x = x, y = y)) + geom_line() + stat_peaks(col = "red") + stat_valleys(col = "green")