Hi all,
I have this data set:
## Empirical copula
## dt1 = ranking
## dt2 = observed uniform data associated with the ranking
Sample data,
> dt1
S_i R_i
[1,] 7.0 10.0
[2,] 232.5 440.5
[3,] 143.0 141.5
[4,] 272.5 222.0
[5,] 46.0 34.0
[6,] 527.0 483.0
[7,] 420.5 563.5
[8,] 23.5 16.5
[9,] 56.5 68.5
[10,] 341.5 382.5
> dt2
unisk1 unisk2
[1,] 0.008 0.010
[2,] 0.298 0.615
[3,] 0.194 0.187
[4,] 0.357 0.297
[5,] 0.067 0.048
[6,] 0.767 0.687
[7,] 0.573 0.805
[8,] 0.032 0.025
[9,] 0.082 0.094
[10,] 0.452 0.516
for S_i data below, I have divided by 691:
> cbind(dt1/(691+1),dt2)
S_i R_i unisk1 unisk2
[1,] 0.01011561 0.01445087 0.008 0.010
[2,] 0.33598266 0.63656069 0.298 0.615
[3,] 0.20664740 0.20447977 0.194 0.187
[4,] 0.39378613 0.32080925 0.357 0.297
[5,] 0.06647399 0.04913295 0.067 0.048
[6,] 0.76156069 0.69797688 0.767 0.687
[7,] 0.60765896 0.81430636 0.573 0.805
[8,] 0.03395954 0.02384393 0.032 0.025
[9,] 0.08164740 0.09898844 0.082 0.094
[10,] 0.49349711 0.55274566 0.452 0.516
My code is
n <- 691
Cn_u1.u2 <- function(dt1,dt2,n)
{ cn <- vector(length=n, mode="numeric")
for (i in 1:n)
{ A <- as.numeric(dt1[i,1]/(n+1) <= dt2[1,1] & dt1[i,2]/(n+1) <=
dt2[1,2])
cn[i] <- sum(A)/n
}
cn
}
What I want to do is to compare all ranking value with each uni data at a time
using logical and if the it is true=1 and else =0. I use as.numeric() as what
you suggested before.
For example: calculate all where ( S_i <= unisk1[1] and R_i <= unisk2[1]) and
continue the process for all unisk1 and unisk2. If n=691, I will have cn=691.
Thank you so much for your help.
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