Example
This is a basic example:
library(kneedle)
#> Registered S3 method overwritten by 'quantmod':
#> method from
#> as.zoo.data.frame zoo
# The base function assumes the graph is both concave and increasing.
# First and second inputs must be vectors of integers or doubles.
plot(c(1,2,3,4,5,6), c(0,1,2,3,40,100), xlab = "x", ylab = "y", pch=21, col="blue", bg="lightblue", type = "b")
Parameters
This describes a few of the parameters that can be changed.
library(kneedle)
#Concavity parameter must be changed if the graph is convex. Furthermore, you
#must specify if the y is increasing or decreasing as x increases.
plot(c(1,2,3,4,5), c(0,20,40,41,42), xlab = "x", ylab = "y", pch=21, col="blue", bg="lightblue", type = "b")
knee <- kneedle(c(1,2,3,4,5), c(0,20,40,41,42), concave = FALSE, decreasing = FALSE)
print(knee)
#> [1] 3 40
plot(c(1,2,3,4,5), c(100,99,98,50,0), xlab = "x", ylab = "y", pch=21, col="blue", bg="lightblue", type = "b")
Sensitivity
This describes how the sensitivity parameter affects the output.
library(kneedle)
# Sensitivity defaults to 1 as per the referenced paper. However, you can adjust
# it. A higher sensitivity make the rules more 'stringent' in classifying a
# 'candidate knee' point as a knee.
plot(c(1,2,3,4,5), c(0,1,2,40,60), xlab = "x", ylab = "y", pch=21, col="blue", bg="lightblue", type = "b")
knee <- kneedle(c(1,2,3,4,5), c(0,1,2,40,60), sensitivity = 1)
print(knee)
#> [1] 3 2
# In this case with sensitivity = 2, we see that that (3,2) is no longer considered a knee point. No
# other knees were detected.
plot(c(1,2,3,4,5), c(0,1,2,40,60), xlab = "x", ylab = "y", pch=21, col="blue", bg="lightblue", type = "b")