Applying a function to a vector

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.

Florent
have a look at:
help(sapply)

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

Thanks for your help

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.

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.

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

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.


 	-thomas

Florent
have a look at:
help(sapply)

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

Thanks for your help