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rauc

How to calculate the AUC of a graph in R?


I have a dataframe (gdata) with x (as "r") and y (as "km") coordinates of a function. When I plot it like this:

    plot(x = gdata$r, y = gdata$km, type = "l")

I get the graph of the function: enter image description here

Now I want to calculate the area under the curve from x = 0 to x = 0.6. When I look for appropriate packages I only find something like calculation AUC of a ROC curve. But is there a way just to calculate the AUC of a normal function?


Solution

  • The area under the curve (AUC) of a given set of data points can be archived using numeric integration:

    Let data be your data frame containing x and y values. You can get the area under the curve from lower x0=0 to upper x1=0.6 by integrating the function, which is linearly approximating your data.

    This is a numeric approximation and not exact, because we do not have an infinite number of data points: For y=sqrt(x) we will get 0.3033 instead of true value of 0.3098. For 200 rows in data we'll get even better with auc=0.3096.

    library(tidyverse)
    
    data <-
      tibble(
      x = seq(0, 2, length.out = 20)
    ) %>%
      mutate(y = sqrt(x))
    data
    #> # A tibble: 20 × 2
    #>        x     y
    #>    <dbl> <dbl>
    #>  1 0     0    
    #>  2 0.105 0.324
    #>  3 0.211 0.459
    #>  4 0.316 0.562
    #>  5 0.421 0.649
    #>  6 0.526 0.725
    #>  7 0.632 0.795
    #>  8 0.737 0.858
    #>  9 0.842 0.918
    #> 10 0.947 0.973
    #> 11 1.05  1.03 
    #> 12 1.16  1.08 
    #> 13 1.26  1.12 
    #> 14 1.37  1.17 
    #> 15 1.47  1.21 
    #> 16 1.58  1.26 
    #> 17 1.68  1.30 
    #> 18 1.79  1.34 
    #> 19 1.89  1.38 
    #> 20 2     1.41
    
    qplot(x, y, data = data)
    

    integrate(approxfun(data$x, data$y), 0, 0.6)
    #> 0.3033307 with absolute error < 8.8e-05
    

    Created on 2021-10-03 by the reprex package (v2.0.1)

    The absolute error returned by integrate is corerect, iff the real world between every two data points is a perfect linear interpolation, as we assumed.