[R] Vectorizing integrate()
David L Carlson
dcarlson at tamu.edu
Thu Dec 6 20:18:17 CET 2012
You can't vectorize the loop because integrate() is not vectorized, but you
really need to pass only one index variable if you redefine your function so
that you are not re-creating it for each step in the loop. That would let
you use sapply(). Here's a toy example that should generalize to your
problem:
> v <- 1:5
> w <- rep(1, 5)
> fun <- function(x, m, n) n*exp(-m*x)
> eta <- sapply(1:5, function(i) integrate(fun, 0, Inf, m=v[i],
n=w[i])$value)
> eta
[1] 1.0000000 0.5000000 0.3333333 0.2500000 0.2000000
Creating the function outside the loop should speed things up.
----------------------------------------------
David L Carlson
Associate Professor of Anthropology
Texas A&M University
College Station, TX 77843-4352
> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
> project.org] On Behalf Of David Winsemius
> Sent: Thursday, December 06, 2012 12:59 PM
> To: Doran, Harold
> Cc: r-help at r-project.org
> Subject: Re: [R] Vectorizing integrate()
>
>
> On Dec 6, 2012, at 10:10 AM, Doran, Harold wrote:
>
> > I have written a program to solve a particular logistic regression
> problem using IRLS. In one step, I need to integrate something out of
> the linear predictor. The way I'm doing it now is within a loop and it
> is as you would expect slow to process, especially inside an iterative
> algorithm.
> >
> > I'm hoping there is a way this can be vectorized, but I have not
> found it so far. The portion of code I'd like to vectorize is this
> >
> > for(j in 1:nrow(X)){
> > fun <- function(u) 1/ (1 + exp(- (B[1] + B[2] * (x[j] + u)))) *
> dnorm(u, 0, sd[j])
> > eta[j] <- integrate(fun, -Inf, Inf)$value
> > }
> >
>
> The Vectorize function is just a wrapper to mapply. If yoou are able to
> get that code to execute properly for your un-posted test cases, then
> why not use mapply?
>
>
> > Here X is an n x p model matrix for the fixed effects, B is a vector
> with the estimates of the fixed effects at iteration t, x is a
> predictor variable in the jth row of X, and sd is a variable
> corresponding to x[j].
> >
> > Is there a way this can be done without looping over the rows of X?
> >
> > Thanks,
> > Harold
> >
> > [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > R-help at r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide http://www.R-project.org/posting-
> guide.html
> > and provide commented, minimal, self-contained, reproducible code.
>
> David Winsemius, MD
> Alameda, CA, USA
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-
> guide.html
> and provide commented, minimal, self-contained, reproducible code.
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