Re: [R] Applying a function to a vector

On Mon, 31 Oct 2005, Thomas Lumley wrote:

> On Mon, 31 Oct 2005, Florent Bresson wrote:
>
>> I just have a try with sapply. The problem is that my
>> function pbeta2 has two parameters z and p (wich is a
>> vector of two parameters). If I use sapply , R returns
>> a message incicating that parameter p is missing. It
>> is a problem since both z and p are varying along my
>> data.frame.
>
> You would need mapply(). It won't help, though. Most of the time is
> presumably being spent in all the calls to integrate, so mapply() or sapply()
> won't be much faster than a loop.
>
>
> According to Google, the VGAM R package http://www.stat.auckland.ac.nz/~yee/
> claims to have the beta distributions of the second kind.

It has ML fitting for such distributions.

I think a reasonable answer is to make a function to approximate the indefinite integral via linear or spline interpolation. Then you can replace 22,000 numerical integrations by interpolation from a few hundred values (at most).

>>> On Mon, 31 Oct 2005, Florent Bresson wrote:
>>
>>>> beta distribution of the second kind (the existing
>>>> beta distribution of th stats package is the beta
>>>> distribution of the first kind). It works perfectly
>>>> for a single value, but I want to apply it to a
>> vector
>>>> of 22 000 values. I can use a loop for the
>> calculation
>>>> of each value but it runs very very slowly.
>>>> So, what can I change ?
>>>>
>>>> Here's the function :
>>>> p <- c(1,1)
>>>> y <- 1
>>>> z <- 1
>>>> truc <- function(y)
>> {y^(p[1]-1)/(1+y)^(p[1]+p[2])}
>>>> pbeta2 <- function(z,p)
>>>> 1/beta(p[1],p[2])*integrate(truc,0,z)$value
>>>>
>>>> machin <- pbeta2(vector,p) just return a single
>> value

-- 
Brian D. Ripley,                  ripley@stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

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