Must be a cut and paste issue. All three agree on the results but they are
different from those in arun's message:
B <- c(0,1)
sem1 = runif(10, 1, 2)
x <- rnorm(10)
X <- cbind(1, x)
eta <- numeric(10)
for(j in 1:nrow(X)){
+ fun <- function(u) 1/ (1 + exp(- (B[1] + B[2] * (x[j] + u)))) * dnorm(u,
0, sem1[j])
+ eta[j] <- integrate(fun, -Inf, Inf)$value
+ }
eta
[1] 0.6586459 0.5565611 0.5226462 0.6824012 0.6908079 0.7578524 0.4715976
[8] 0.2165210 0.2378657 0.3492133
fun <- function(u, m, s) 1/ (1 + exp(- (B[1] + B[2] *
+ (m + u)))) * dnorm(u, 0, s)
eta2 <- sapply(1:nrow(X), function(i) integrate(fun,
+ -Inf, Inf, m=x[i], s=sem1[i])$value)
eta2
[1] 0.6586459 0.5565611 0.5226462 0.6824012 0.6908079 0.7578524 0.4715976
[8] 0.2165210 0.2378657 0.3492133
identical(eta, eta2)
[1] TRUE
res<-mapply(function(i)
integrate(fun,-Inf,Inf,m=x[i],s=sem1[i])$value,1:nrow(X))
res
[1] 0.6586459 0.5565611 0.5226462 0.6824012 0.6908079 0.7578524 0.4715976
[8] 0.2165210 0.2378657 0.3492133
identical(eta, res)
[1] TRUE
-------
David C
-----Original Message-----
From: arun [mailto:[email protected]]
Sent: Friday, December 07, 2012 10:36 AM
To: Doran, Harold
Cc: R help; David L Carlson; David Winsemius
Subject: Re: [R] Vectorizing integrate()
Hi,
Using David's function:
fun <- function(u, m, s) 1/ (1 + exp(- (B[1] + B[2] *
(m + u)))) * dnorm(u, 0, s)
res<-mapply(function(i) integrate(fun,-
Inf,Inf,m=x[i],s=sem1[i])$value,1:nrow(X))
res
# [1] 0.5212356 0.6214989 0.5306124 0.5789414 0.3429795 0.6972879
0.5952949
#[8] 0.7531899 0.4740685 0.7576587
identical(res,eta)
#[1] TRUE
A.K.
----- Original Message -----
From: "Doran, Harold" <[email protected]>
To: David Winsemius <[email protected]>
Cc: "[email protected]" <[email protected]>
Sent: Friday, December 7, 2012 10:14 AM
Subject: Re: [R] Vectorizing integrate()
David et al
Thanks, I should have made the post more complete. I routinely use
apply functions, but often avoid mapply() as I find it so non-
intuitive. In this instance, I think the situation demands I change
that position, though.
Reproducible code for the current implementation of the function is
B <- c(0,1)
sem1 = runif(10, 1, 2)
x <- rnorm(10)
X <- cbind(1, x)
eta <- numeric(10)
for(j in 1:nrow(X)){
fun <- function(u) 1/ (1 + exp(- (B[1] + B[2] * (x[j] + u)))) *
dnorm(u, 0, sem1[j])
eta[j] <- integrate(fun, -Inf, Inf)$value
}
I can't get my head around how mapply() would work here. It accepts as
its first argument a function. But, in my case I have two functions:
the user defined integrand, fun(), an then of course calling the R
function integrate().
I was thinking maybe along these lines, but this is obviously wrong.
mapply(integrate(function(u) 1/ (1 + exp(- (B[1] + B[2] * (x + u)))) *
dnorm(u, 0, sem1), -Inf, Inf)$value, MoreArgs = list(B, x, sem1))
-----Original Message-----
From: David Winsemius [mailto:[email protected]]
Sent: Thursday, December 06, 2012 1:59 PM
To: Doran, Harold
Cc: [email protected]
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]]
______________________________________________
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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
______________________________________________
[email protected] 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.
