[R-SIG-Finance] Use apply/lapply/tapply functions
Jorge Nieves
jorge.nieves at moorecap.com
Wed Sep 3 17:58:21 CEST 2008
Thanks for your suggestions.
I just started using R recently. I am trying to figure out my way around the system. I tested your suggestions and the speed of "apply" is definitely better that of the "for" loop.
The two function inputs (out of a total five) that I am trying to parameterize (loop trough) are not time dependent. Therefore, I believe I could use some function from the apply family, but I do not know how to set it up. The references in the help do not show how to select ONLY a subset (two in his case) of the variables that go into my function. Say if the function takes in (x1,p1,p2,y1,y2), my problem is to determine how to APPLY p1 and p2 only?
What will be the equivalent in the APPLY space to the following for loop code?
for p1 in 1:100
{
for p2 in 1:100
{
test = myfunction(x1,p1,p2,y1,y2)
}
}
Where:
myfunction = function (dataset, p1,p2,y1,y2,y3)
{
Line1
Line2
Line3
::::::::
:::::::
:::::::
Return(res.table)
}
res.table is a n by m matrix
Jorge
-----Original Message-----
From: Enrico Schumann [mailto:enricoschumann at yahoo.de]
Sent: Wednesday, September 03, 2008 11:28 AM
To: 'Rob Steele'; Jorge Nieves
Cc: r-sig-finance at stat.math.ethz.ch
Subject: AW: [R-SIG-Finance] Use apply/lapply/tapply functions
i suppose that this is rather an r-help question; however, if you can use a function from the ``apply-family'', it should usually be far faster than a loop.
try
N <- 100000
x <- array(0,dim=c(N,1))
set.seed(1284357)
# loop
pcm <- proc.time()
for (i in 1:N){
x[i] <- rnorm(1)
}
p1 <- proc.time()-pcm
set.seed(1284357)
# apply
y <- array(0,dim=c(N,1))
pcm <- proc.time()
y <- apply(y,2,rnorm)
p2 <- proc.time()-pcm
# compare time needed
p1
p2
# compare results
sum(x!=y)
but, if you can use apply, then you probably did not really need a loop in the first place, as your procedure is not really sequential (in the sense that the computation in i+1 really required the computation from step i)
-----Ursprüngliche Nachricht-----
Von: r-sig-finance-bounces at stat.math.ethz.ch
[mailto:r-sig-finance-bounces at stat.math.ethz.ch] Im Auftrag von Rob Steele
Gesendet: Mittwoch, 3. September 2008 16:52
An: r-sig-finance at stat.math.ethz.ch
Betreff: Re: [R-SIG-Finance] Use apply/lapply/tapply functions
The looping functions (apply/lapply/tapply) can make your code cleaner and easier to read but they can't speed it up. For that you need to make the stuff in the loop faster, perhaps by vectorizing parts you're currently doing serially.
Jorge Nieves wrote:
> Hi,
>
> I have a function that takes in a dataset ( a matrix of m rows by n
> columns), and five additional "constant" parameters, p1,p2,y1,y2,y3.
> The function perform a series of operations and transformations on the
> dataset, and returns a table of results.
>
> I have tested the function repeatedly and it works fine.
>
> However, I would like to generate a grid of results from myfunction
> for different values of two of the input parameters: p1, and p2.
>
> I have tried using for loops, and they work, but the computation time
> is a too long. I would like to use the apply/lapply/tapply functions
> to avoid using for loops, what ever works !!!
>
> Can someone recommend how to use these function to parameterize only a
> subset of the inputs into the function, i.e p1, and p2?
>
> Any tips/recommendations will be appreciated.
>
>
>
> myfunction = function (dataset, p1,p2,y1,y2,y3) {
>
> Line1
> Line2
> Line3
> ::::::::
> :::::::
> :::::::
> Return(res.table)
> }
>
>
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