Re: [R] Multivariate function from univariate functions
Petr, thanks! I've now got a function I can work with. Regards! -- View this message in context: http://r.789695.n4.nabble.com/Multivariate-function-from-univariate-functions-tp4502670p4504599.html Sent from the R help mailing list archive at Nabble.com. __ R-help@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.
[R] Multivariate function from univariate functions
I'm relatively new to R and I'm stuck.
I'm trying to construct a surface to optimize from a multivariate dataset.
The dataset contains the response of a system to various stimuli. I am
trying to optimize the mix of stimuli to maximize the response. To do so,
I've interpolated the various datasets of type response vs. stimuli and I
now have an array of functions interps whose length is the length of the
array of the names of the various stimuli. I've also created a vector
containing names for the stimuli, vars = x.1, x.2, x.3...
Anyway, each of the functions in interps depends only on one variable
(obviously). I would like to construct a function, call it, surface which
is essentially: surface(vars) = interps[[1]]vars[[1]] +
interps[[2]]vars[[2]]+...
I've tried constructing surface recursively in a for loop:
surface - function(vars){0}
for(i in 1:length(vars)){
surface - function(vars){surface(vars) + interps[[i]](vars[[i]])}
}
This results in an infinite recursion error...which I think I understand.
Essentially, I'm trying to do the analog of something like i = i+1, but
instead of adding integers, I want to add terms to a function.
Any help is appreciated.
--
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Re: [R] Multivariate function from univariate functions
Naïve question: would a saturated multivariate model work as an
interpolation function?
On 3/24/12, physicistintheory physicistinthe...@gmail.com wrote:
I'm relatively new to R and I'm stuck.
I'm trying to construct a surface to optimize from a multivariate dataset.
The dataset contains the response of a system to various stimuli. I am
trying to optimize the mix of stimuli to maximize the response. To do so,
I've interpolated the various datasets of type response vs. stimuli and I
now have an array of functions interps whose length is the length of the
array of the names of the various stimuli. I've also created a vector
containing names for the stimuli, vars = x.1, x.2, x.3...
Anyway, each of the functions in interps depends only on one variable
(obviously). I would like to construct a function, call it, surface which
is essentially: surface(vars) = interps[[1]]vars[[1]] +
interps[[2]]vars[[2]]+...
I've tried constructing surface recursively in a for loop:
surface - function(vars){0}
for(i in 1:length(vars)){
surface - function(vars){surface(vars) + interps[[i]](vars[[i]])}
}
This results in an infinite recursion error...which I think I understand.
Essentially, I'm trying to do the analog of something like i = i+1, but
instead of adding integers, I want to add terms to a function.
Any help is appreciated.
--
View this message in context:
http://r.789695.n4.nabble.com/Multivariate-function-from-univariate-functions-tp4502670p4502670.html
Sent from the R help mailing list archive at Nabble.com.
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Re: [R] Multivariate function from univariate functions
On Sat, Mar 24, 2012 at 08:04:49PM -0700, physicistintheory wrote:
I'm relatively new to R and I'm stuck.
I'm trying to construct a surface to optimize from a multivariate dataset.
The dataset contains the response of a system to various stimuli. I am
trying to optimize the mix of stimuli to maximize the response. To do so,
I've interpolated the various datasets of type response vs. stimuli and I
now have an array of functions interps whose length is the length of the
array of the names of the various stimuli. I've also created a vector
containing names for the stimuli, vars = x.1, x.2, x.3...
Anyway, each of the functions in interps depends only on one variable
(obviously). I would like to construct a function, call it, surface which
is essentially: surface(vars) = interps[[1]]vars[[1]] +
interps[[2]]vars[[2]]+...
I've tried constructing surface recursively in a for loop:
surface - function(vars){0}
for(i in 1:length(vars)){
surface - function(vars){surface(vars) + interps[[i]](vars[[i]])}
}
Hi.
Is the following close to what you are asking for?
f1 - function(x) 3*x^2 + x
f2 - function(x) 2*x^2 + 2*x
f3 - function(x) x^2 + 3*x
lstf - list(f1, f2, f3)
args - c(x2, x4, x5)
# input as a matrix or data frame
surface - function(dat)
{
y - rep(0, times=nrow(dat))
for (i in seq.int(along=lstf)) {
y - y + lstf[[i]](dat[, args[i]])
}
y
}
dat - matrix(1:35, ncol=5)
colnames(dat) - paste(x, 1:5, sep=)
surface(dat)
[1] 2140 2346 2564 2794 3036 3290 3556
# compare with an explicit formula
f1(dat[, x2]) + f2(dat[, x4]) + f3(dat[, x5])
[1] 2140 2346 2564 2794 3036 3290 3556
# input as a named vector
surface1 - function(x)
{
y - 0
for (i in seq.int(along=lstf)) {
y - y + lstf[[i]](x[args[i]])
}
unname(y)
}
vdat - 1:5
names(vdat) - paste(x, 1:5, sep=)
surface1(vdat)
[1] 94
# compare again
unname(f1(vdat[x2]) + f2(vdat[x4]) + f3(vdat[x5]))
[1] 94
Hope this helps.
Petr Savicky.
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