Thanks to all who responded,
I've found a very useful code here:
http://courses.washington.edu/fish507/notes.html
In particular the Lecture 3...
Héctor
2015-10-17 7:05 GMT+00:00 Berend Hasselman :
>
> Your model is producing -Inf entries in the vector Be (in function modl
> and LL) at some s
Your model is producing -Inf entries in the vector Be (in function modl and LL)
at some stage during the optimization process.
You should first do something about that before anything else.
Berend
> On 17 Oct 2015, at 03:01, Bert Gunter wrote:
>
> I made no attempt to examine your details fo
I made no attempt to examine your details for problems, but in general,
My problem
> is that the results change a lot depending on the initial values... I can't
> see what I am doing wrong...
>
> This is a symptom of an overparameterized model: The parameter estimates
> are unstable even though t
Dear R users,
I'im trying to find the parameters of a dynamic biomass model using maximum
likelihood estimation. I used two approaches, one by hand, with optim()
function and the other using mle2() function from package bbmle. My problem
is that the results change a lot depending on the initial va
Hello,
You cannot change the numerical accuracy, it's a built-in constant. To
see it use
?.Machine
.Machine$double.eps # smallest value different from zero
Actually, .Machine$double.eps is the "the smallest positive
floating-point number x such that 1 + x != 1"
You can try the following
Rui, thanks for your reply. You meant that it is the issue of accuracy? So if
I change the numerical accuracy, my results can be output? Thanks a lot!
--
View this message in context:
http://r.789695.n4.nabble.com/Optimization-problem-tp4663821p4663928.html
Sent from the R help mailing list arc
Hello,
Your thoght is mathematically right but numerically wrong. The result
given by optimize is so close to the real minimum that numerical
accuracy comes in and it becomes indistinguishable from the value you're
expecting.
You get the minimum up to a certain accuracy, not more.
Hope this
Thank you professor. I think the minimum value of x^2 between -1 and 1 should
be x=0, y=0. but the result is not that. I am thinking is any wrong with my
thought?
Thanks for helping me out!
--
View this message in context:
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On Apr 10, 2013, at 03:24 , nntx wrote:
> As a simple example, I want to find minimum value for x^2, but it can't be
> obtained by:
> f<-function(x)x^2
> optimize(f,lower=-1,upper=1)
Works fine for me. What did you expect it to do?
> f<-function(x)x^2
> optimize(f,lower=-1,upper=1)
$minimum
[1]
As a simple example, I want to find minimum value for x^2, but it can't be
obtained by:
f<-function(x)x^2
optimize(f,lower=-1,upper=1)
What are other methods to deal with this? I tried DEoptim, still doesn't
work. Any suggustions will be extremely helpful! THanks!
Shelly
--
View this message
On 09-02-2013, at 21:08, Axel Urbiz wrote:
> Dear List,
>
> I'm new in R. I'm trying to solve a simple constrained optimization
> problem.
>
> Essentially, let's say I have a matrix as in the object 'mm' inside the
> function below. My objective function should have a matrix of parameters,
> o
Dear List,
I'm new in R. I'm trying to solve a simple constrained optimization
problem.
Essentially, let's say I have a matrix as in the object 'mm' inside the
function below. My objective function should have a matrix of parameters,
one parameter for each element 'mm' (4 in this case). The prob
Hi Greg,
The problem is that I also have restrictions for each variable (they must be
higher than -.07 and smaller than .2) and I'm dealing with a lot of them.
I've already tried the second approach but, as far as it seems, the function
doesn't satisfy my objective.
That's what I'm doing:
...
There are a couple of options.
First if you want the mean to equal 7, then that means the sum must
equal 21 and therefore you can let optim only play with 2 of the
variables, then set the 3rd to be 21-s1-s2.
If you want the mean to be greater than 7 then just put in a test, if
the mean is less th
Hi,
I'm dealing with an optimization problem. I'm using 'optim' to maximize the
output of a function, given some restrictions on the input. I would like to
know if there is a way to impose some restrictions on 'intermediate
variables' of the function. An example..
fx = function (x)
{
s <- 0
for (
Sent: Wednesday, July 28, 2010 11:11 AM
To: r-h...@stat.math.ethz.ch
Subject: Re: [R] Optimization problem with nonlinear constraint
Uli Kleinwechter uni-hohenheim.de> writes:
>
> Dear Ravi,
>
> As I've already written to you, the problem indeed is to find a solution
>
--
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of Hans W Borchers
Sent: Wednesday, July 28, 2010 11:11 AM
To: r-h...@stat.math.ethz.ch
Subject: Re: [R] Optimization problem with nonlinear constraint
Uli Kleinwechter uni-hohenheim.de> writes:
>
> Dear
Uli Kleinwechter uni-hohenheim.de> writes:
>
> Dear Ravi,
>
> As I've already written to you, the problem indeed is to find a solution
> to the transcendental equation y = x * T^(x-1), given y and T and the
> optimization problem below only a workaround.
I don't think optimization is the ri
help@r-project.org
Subject: [R] Optimization problem with nonlinear constraint
Dear all,
I'm looking for a way to solve a simple optimization problem with a
nonlinear constraint. An example would be
max x s.t. y = x * T ^(x-1)
where y and T are known values.
optim() and constrOpti
now if you run into any problems using it.
Best,
Ravi.
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of Uli Kleinwechter
Sent: Monday, July 26, 2010 10:16 AM
To: r-help@r-project.org
Subject: [R] Optimization problem with nonlinear
Dear all,
I'm looking for a way to solve a simple optimization problem with a
nonlinear constraint. An example would be
max x s.t. y = x * T ^(x-1)
where y and T are known values.
optim() and constrOptim() do only allow for box or linear constraints,
so I did not succedd here. I als
> I don't see why one would want to pretend that the function is continuous.
It isn't.
> The x variable devices is discrete.
> Moreover, the whole solution space is small: the possible solutions are
integers in the range of maybe 20-30.
Yes, you are right, what I'd like to think is that the outco
I don't see why one would want to pretend that the function is
continuous. It isn't.
The x variable devices is discrete.
Moreover, the whole solution space is small: the possible solutions
are integers in the range of maybe 20-30.
Bill
On Fri, Jun 18, 2010 at 9:00 AM, José E. Lozano wrote:
>
>>>
>> How about smoothing the percentages, and then take the second
>> derrivative to find the inflection point?
>>
>> which.max(diff(diff((lowess(percentages)$y
>
> This solution is what I've been using so far. The only difference is that
I am smoothing the 1st derivative, since its
> the one
Hello:
> Here is a general approach using smoothing using the Gasser-Mueller
kernel,
> which is implemented in the "lokern" package. The optimal bandwidth for
> derivative estimation is automatically chosen using a plug-in
approximation.
> The code and the results are attached here.
Maybe am I
> How about smoothing the percentages, and then take the second derrivative
to find the inflection point?
>
> which.max(diff(diff((lowess(percentages)$y
This solution is what I've been using so far. The only difference is that I
am smoothing the 1st derivative, since its the one I want to be s
Sorry, thought you wanted to find lowest value of x that produced
maximum value of y. I see now that is not the case.
I think you have to decide on what amount of improvement per device
you judge to be 'minimal'. Then the algorithm uses the value of y that
occurs at the point where this criterion
f you have any questions.
Ravi.
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of José E. Lozano
Sent: Thursday, June 17, 2010 7:48 AM
To: r-help@r-project.org
Subject: [R] Optimization problem
Hello,
I'm facing a problem of opt
min(devices[percentages==max(percentages)])
Bill
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contain
How about smoothing the percentages, and then take the second derrivative to
find the inflection point?
which.max(diff(diff((lowess(percentages)$y
Bart
--
View this message in context:
http://r.789695.n4.nabble.com/Optimization-problem-tp2258654p2258828.html
Sent from the R help mailing l
Hello,
I'm facing a problem of optimization, I've already solved but I'm trying to
find other answers to this problem to improve the solution.
Well, to make it short: I have to set/install a number of devices in a
building, and I have to give service to a number of "customers", or better
say, to
Dear R users,
I need some advises on how to use R to optimize this function with the
following constraints.
f(x1,x2,x3,y1,y2,y3,)
= gamma(x1+x2-1)/{gamma(x1)*gamma(x2)} * y1^(x2-1) * y2^(x1-1)
+ gamma(x1+x3-1)/{gamma(x1)*gamma(x3)} * y1^(x3-1) * y3^(x1-1)
+ gamma(x2+x3-1)/{gamma(x2)*gamma(x3)
Ravi Varadhan jhmi.edu> writes:
>
> Dear Hans,
>
> I agree with your comments. My intuition was that the quadratic
> form would be better behaved than the radical form (less
> nonlinear!?). So, I was "hoping" to see a change in behavior when
> the cost function was altered from a radical (i.
gt; Ravi Varadhan, Ph.D.
> Assistant Professor,
> Division of Geriatric Medicine and Gerontology
> School of Medicine
> Johns Hopkins University
>
> Ph. (410) 502-2619
> email: rvarad...@jhmi.edu
>
>
> - Original Message -
> From: Erwin Kalvelagen
&
klau...@gmx.de
Date: Sunday, January 17, 2010 8:06 am
Subject: Re: [R] optimization problem
To: Ravi Varadhan , erwin.kalvela...@gmail.com,
hwborch...@googlemail.com
Cc: r-h...@stat.math.ethz.ch
> Dear Erwin, Ravi and Hans Werner,
>
> thanks a lot for your replies. I don't think
atric Medicine and Gerontology
School of Medicine
Johns Hopkins University
Ph. (410) 502-2619
email: rvarad...@jhmi.edu
- Original Message -
From: "Hans W. Borchers"
Date: Sunday, January 17, 2010 3:54 am
Subject: Re: [R] optimization problem
To: r-h...@stat.math.eth
hey can be used?
Thank a lot again!
Klaus
Original-Nachricht
> Datum: Sat, 16 Jan 2010 23:42:08 -0500
> Von: Ravi Varadhan
> An: Erwin Kalvelagen
> CC: r-h...@stat.math.ethz.ch
> Betreff: Re: [R] optimization problem
>
> Interesting!
>
> Now, if I
Ravi Varadhan jhmi.edu> writes:
>
> Interesting!
>
> Now, if I change the "cost matrix", D, in the LSAP formulation slightly
> such that it is quadratic, it finds the best solution to your example:
Dear Ravi,
I thought your solution is ingenious, but after the discussion with
Erwin Kalvela
.edu
- Original Message -
From: Erwin Kalvelagen
Date: Saturday, January 16, 2010 5:26 pm
Subject: Re: [R] optimization problem
To: Ravi Varadhan
Cc: r-h...@stat.math.ethz.ch
> I believe this is a very good approximation but not a 100% correct
> formulation of the original p
dhan, Ph.D.
> Assistant Professor,
> Division of Geriatric Medicine and Gerontology
> School of Medicine
> Johns Hopkins University
>
> Ph. (410) 502-2619
> email: rvarad...@jhmi.edu
>
>
> - Original Message -
> From: Erwin Kalvelagen
> Date: Saturday,
f Geriatric Medicine and Gerontology
School of Medicine
Johns Hopkins University
Ph. (410) 502-2619
email: rvarad...@jhmi.edu
- Original Message -
From: Erwin Kalvelagen
Date: Saturday, January 16, 2010 1:36 pm
Subject: Re: [R] optimization problem
To: Ravi Varadhan
Cc: r-h...@stat.math
Ph.D.
> Assistant Professor,
> Division of Geriatric Medicine and Gerontology
> School of Medicine
> Johns Hopkins University
>
> Ph. (410) 502-2619
> email: rvarad...@jhmi.edu
>
>
> - Original Message -
> From: Erwin Kalvelagen
> Date: Saturday, January
cine
Johns Hopkins University
Ph. (410) 502-2619
email: rvarad...@jhmi.edu
- Original Message -
From: Ravi Varadhan
Date: Saturday, January 16, 2010 10:00 am
Subject: Re: [R] optimization problem
To: Erwin Kalvelagen
Cc: r-h...@stat.math.ethz.ch
> Thanks, Erwin, for pointing out th
January 16, 2010 2:35 am
Subject: Re: [R] optimization problem
To: r-h...@stat.math.ethz.ch
> Ravi Varadhan jhmi.edu> writes:
> > dist <- function(A, B) {
> > # Frobenius norm of A - B
> > n <- nrow(A)
> > sum(abs(B - A))
> > }
> >
>
&
Ravi Varadhan jhmi.edu> writes:
> dist <- function(A, B) {
> # Frobenius norm of A - B
> n <- nrow(A)
> sum(abs(B - A))
> }
>
See http://mathworld.wolfram.com/FrobeniusNorm.html for a definition of the
Frobenius norm.
Erwin
--
Ravi Varadhan, Ph.D.
Assistant Professor,
Division of Geriatric Medicine and Gerontology
School of Medicine
Johns Hopkins University
Ph. (410) 502-2619
email: rvarad...@jhmi.edu
- Original Message -
From: klau...@gmx.de
Date: Friday, January 15, 2010 9:53 am
Sub
gmx.de> writes:
>
> Dear R-experts,
>
> this is not a direct R-problem but I hope you can help me anyway.
>
> I would like to minimize || PG-I || over P, where P is a p x p permutation
matrix (obtained by permuting the rows
> and/or columns of the identity matrix), G is a given p x p matrix
Dear R-experts,
this is not a direct R-problem but I hope you can help me anyway.
I would like to minimize || PG-I || over P, where P is a p x p permutation
matrix (obtained by permuting the rows and/or columns of the identity matrix),
G is a given p x p matrix with full rank and I the identity
Note your problem is equivalent to the unconstrained problem:
f(a1^2 / (a1^2 + a2^2), a2^2 / (a1^2 + a2^2), x3, x4, a3^2, a4^2)
optimizing over a1, a2, a3, a4, x3, x4. See the optimization task view
for specific functions:
http://cran.r-project.org/web/views/Optimization.html
On Sat, Oct
ge: 27
> Date: Sat, 17 Oct 2009 13:50:10 -0700 (PDT)
> From: kathie
> Subject: [R] optimization problem with constraints...
> To: r-help@r-project.org
> Message-ID: <25941686.p...@talk.nabble.com>
> Content-Type: text/plain; charset=us-ascii
>
>
> Dear R users,
&
Dear R users,
I need some advises on how to use R to optimize a nonlinear function with
the following constraints.
f(x1,x2,x3,x4,x5,x6)
s.t
0 < x1 < 1
0 < x2 < 1
0 < x1+x2 < 1
-inf < x3 < inf
-inf < x4 < inf
0 < x5 < inf
0 < x6 < inf
Is there any built-in function or something for these co
In case anyone is still reading this thread, I want to add this:
In a current problem (a data-shy five-parameter nonlinear
optimization), I found "nlminb" markedly more reliable than
"optim" with method "L-BFGS-B". In reviewing the fit I made, I
found that "optim" only came close to its own minimum
"Hans W. Borchers" <[EMAIL PROTECTED]> wrote:
> Why not use one of the global optimizers in R, for instance 'DEoptim', and
> then apply optim() to find the last six decimals? I am relatively sure that
> the Differential Evolution operator has a better chance to come near a
> global optimum than a
Why not use one of the global optimizers in R, for instance 'DEoptim', and
then apply optim() to find the last six decimals? I am relatively sure that
the Differential Evolution operator has a better chance to come near a
global optimum than a loop over optim(), though 'DEoptim' may be a bit slow
tedzzx <[EMAIL PROTECTED]> wrote:
>
> If I want to find out the globle minia, how shoul I change my code?
I sometimes use optim() within a loop, with random starting
values for each iteration of the loop. You can save the
objective function value each time and pick the best solution.
Last time I
tedzzx gmail.com> writes:
>
>
> Hi, all
>
> I am facing an optimization problem. I am using the function optim(par,fun),
> but I find that every time I give different original guess parameter, I can
> get different result. For example
> I have a data frame named data:
> head(data)
>price
If I want to find out the globle minia, how shoul I change my code?
Thanks a lot
Armin Meier wrote:
>
> Hi,
> I guess your function has several local minima and depending on where
> you start, i.e. your initial variables, you get into another mimimum.
>
> HTH
> Armin
>
> __
Subject: [R] optimization problem
To: r-help@r-project.org
Message-ID: <[EMAIL PROTECTED]>
Content-Type: text/plain; charset=UTF-8
I am facing an optimization problem. I am using the function optim(par,fun),
but I find that every time I give different original guess parameter, I can
get
Hi,
I guess your function has several local minima and depending on where
you start, i.e. your initial variables, you get into another mimimum.
HTH
Armin
__
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https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read th
Hi, all
I am facing an optimization problem. I am using the function optim(par,fun),
but I find that every time I give different original guess parameter, I can
get different result. For example
I have a data frame named data:
head(data)
price s x t
1 1678.0 12817 11200 0.14959
le/Faculty/Varadhan.html
-Original Message-
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On
Behalf Of Jiang Peng
Sent: Monday, November 24, 2008 6:28 AM
To: r-help@r-project.org
Subject: [R] op
Peng
Sent: Monday, November 24, 2008 5:28 AM
To: r-help@r-project.org
Subject: [R] optimization problem
Dear list,
hi !
I am a R beginner and I have a function to optimize .
alpha = argmin{ f(x,alpha) }
I want alpha to be in [0,1]. Is there any function that can work?
I use nl
Dear list,
hi !
I am a R beginner and I have a function to optimize .
alpha = argmin{ f(x,alpha) }
I want alpha to be in [0,1]. Is there any function that can work?
I use nlm() but i can't fix the domain of alpha.
thanks in advance
___
Jiang Peng, Ph.D. Cand
I'm trying to da an optimization for the followig function
Zwischenwert <- function (x)
{
lambda<-x[1];
mu<-x[2];
gammal<-x[3];
mud<-x[4];
gammad<-x[5];
Mittelwert <-0;
for(t in 0:(T-1))
{
for(i in 0:(n-1))
Hi,
how can I order the rows and columns of a matrix A to generate B, in order
to minimize the length(rle(B)$lengths) for all the rows and columns ?
> set.seed(5)
> a <- matrix(rnorm(200), nrow=20)
> a[a<=0] <- 0
> a[a>0] <- 1
> a
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,]
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