Using integrate() with vectors as boundaries rather than scalars

I think I have figured it out myself, would however like to know the opinion
of more experienced coders. Is this a "good" way of approaching this:

cumdnorm1 <- function(x) {integrate(dnorm,x,Inf)}

evalvec <- function(x) {lapply(x,cumdnorm1)}

It does return the desired result.



Tobias wrote:

Hi all

my apologies if above title is misleading, but here is my problem anyways:

I need to evaluate an integral n times. Since I can't get my head around
vectorization as of yet, I have coded it up in a loop, i.e.:

for (i in 1:n)

{

    z[i] <- integrate(dnorm,x[i],Inf)

}

Since n is quite large in my operation, ~40000, I would rather stack all
the elements of x into a vector and then evaluate the integral for each
vector element in x up to infinity. So that the operation would look
something like this:

z <- integrate(dnorm,x,Inf)

I am not sure if this works, as I am new to R, however managed the
equivalent in MatLab. Is this possible at all? If yes, your input would be
highly appreciated.

Regards

Tobias

--
View this message in context: http://www.nabble.com/Using-integrate%28%29-with-vectors-as-boundaries-rather-than-scalars-tf2421074.html#a6750170
Sent from the R help mailing list archive at Nabble.com.