Thanks for the suggestions.
I add some more detail to clarify:
h=matrix(nrow=1,ncol=22)
In my data h is:
(0.25 0.25 0 0 0 0 -0.25 -0.25 -0.25 -0.25 -0.5 -0.5 0 0.25 0.25
0.25 0.25 0.25 0.25 0.25 0.25 0.25)
xx<-seq(0,1,0.00005)
v=matrix(nrow=20001,ncol=22)
vv=matrix(nrow=20001,ncol=22)
for (y in 1:20001) {
v[y,22]=h[1,22]
}
vv[20001,22]=v[20001,22]
for(k in 21:1) {
for(j in 20001:2) {
vv[j-1,k+1]=min(xx[j-1]*v[j-1,k+1],vv[j,k+1])
v[j,k]=h[1,k]+vv[j-1,k+1]
}
vv[20001,k]=v[20001,k]
}
The idea of using Rcpp seems to be good. Having never used this package will
give a look.
Somewhere I read an example like this:
for (i in 1:R) {
res[i]<-f()
NULL
}
where f() is a function, but I don't how can I trasform my code:
vv[j-1,k+1]=min(xx[j-1]*v[j-1,k+1],vv[j,k+1])
v[j,k]=h[1,k]+vv[j-1,k+1]
in a function
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