Can any one help how to find approximate area under the curve using Riemann Sums in R?
It seems we do not have any package in R which could help.
Sample data:
MNo1 X1 Y1 MNo2 X2 Y2
1 2981 -66287 1 595 -47797
1 2981 -66287 1 595 -47797
2 2973 -66087 2 541 -47597
2 2973 -66087 2 541 -47597
3 2963 -65887 3 485 -47397
3 2963 -65887 3 485 -47397
4 2952 -65687 4 430 -47197
4 2952 -65687 4 430 -47197
5 2942 -65486 5 375 -46998
5 2942 -65486 5 375 -46998
6 2935 -65286 6 322 -46798
6 2935 -65286 6 322 -46798
7 2932 -65086 7 270 -46598
7 2932 -65086 7 270 -46598
8 2936 -64886 8 222 -46398
8 2936 -64886 8 222 -46398
9 2948 -64685 9 176 -46198
9 2948 -64685 9 176 -46198
10 2968 -64485 10 135 -45999
10 2968 -64485 10 135 -45999
11 2998 -64284 11 97 -45799
11 2998 -64284 11 97 -45799
12 3035 -64084 12 65 -45599
12 3035 -64084 12 65 -45599
13 3077 -63883 13 37 -45399
13 3077 -63883 13 37 -45399
14 3122 -63683 14 14 -45199
14 3122 -63683 14 14 -45199
15 3168 -63482 15 -5 -44999
15 3168 -63482 15 -5 -44999
16 3212 -63282 16 -20 -44799
16 3212 -63282 16 -20 -44799
17 3250 -63081 17 -31 -44599
17 3250 -63081 17 -31 -44599
18 3280 -62881 18 -38 -44399
18 3280 -62881 18 -38 -44399
19 3301 -62680 19 -43 -44199
19 3301 -62680 19 -43 -44199
20 3313 -62480 20 -45 -43999
Check this demo :
> library(zoo)
> x <- 1:10
> y <- -x^2
> Result <- sum(diff(x[x]) * rollmean(y[x], 2))
> Result
[1] -334.5
After check this question, I found function trapz() from package pracma be more efficient:
> library(pracma)
> Result.2 <- trapz(x, y)
> Result.2
[1] -334.5