On Wed, Mar 18, 2009 at 7:43 PM, Berend Hasselman wrote:
>>> system.time(ans.nl <- nleqslv(x=p0, fn=broydt))[1]
>>
>> user.self
>> 8.17
>
> On my Imac 2.16Ghz and R 2.8.1 and Mac OS X 10.5.6
> this took approximately 5 seconds.
>
> Interesting is this experiment.
> I set the jacobian for a star
On 18-03-2009, at 18:36, Ravi Varadhan wrote:
system.time(ans.nl <- nleqslv(x=p0, fn=broydt))[1]
user.self
8.17
On my Imac 2.16Ghz and R 2.8.1 and Mac OS X 10.5.6
this took approximately 5 seconds.
Interesting is this experiment.
I set the jacobian for a starting point with all x-values
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of Paul Smith
Sent: Wednesday, March 18, 2009 10:19 AM
To: r-help@r-project.org
Subject: Re: [R] Non-Linear Optimization - Query
On Tue, Mar 17, 2009 at 7:55 PM, Berend Hasselman wrote:
> You ca
Paul Smith wrote:
>
> On Tue, Mar 17, 2009 at 7:55 PM, Berend Hasselman wrote:
>> You can also try my package "nleqslv" for solving systems of non linear
>> equations (using Broyden or Newton with a selection of global
>> strategies).
>>
>> library(nleqslv)
>>
>> xinit <- rep(1,3)
On Tue, Mar 17, 2009 at 7:55 PM, Berend Hasselman wrote:
> You can also try my package "nleqslv" for solving systems of non linear
> equations (using Broyden or Newton with a selection of global strategies).
>
> library(nleqslv)
>
> xinit <- rep(1,3) # or rep(0,3) for a singular star
Ravi Varadhan wrote:
>
>
> require(BB)
>
> f2 <- function(x) {
> f <- rep(NA, length(x))
> f[1] <- 1 + 2 * x[1] * x[3] # x[3] is the Lagrangian multiplier
> f[2] <- 1 + 2 * x[2] * x[3]
> f[3] <- x[1]^2 + x[2]^2 - 1 # the equality constraint
> f
> }
>
>
You can also try my packag
On Tue, Mar 17, 2009 at 7:10 PM, Ravi Varadhan wrote:
> Here is how you can implement the Lagrangian multiplier approach and solve
> the first-order KKT conditions to obtain the solution for Paul Smith's
> example:
>
> require(BB)
>
> f2 <- function(x) {
> f <- rep(NA, length(x))
> f[1] <-
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of Paul Smith
Sent: Tuesday, March 17, 2009 2:34 PM
To: r-help@r-project.org
Subject: Re: [R] Non-Linear Optimization - Query
Hi Lars,
Consider the following problem:
max x + y
s
uesday, March 17, 2009 2:34 PM
To: r-help@r-project.org
Subject: Re: [R] Non-Linear Optimization - Query
Hi Lars,
Consider the following problem:
max x + y
subject to
x^2 + y^2 =1.
The solution is obviously (x,y) = (sqrt(2) / 2, sqrt(2) / 2).
Now, consider the unconstrained maximization problem o
Hi Lars,
Consider the following problem:
max x + y
subject to
x^2 + y^2 =1.
The solution is obviously (x,y) = (sqrt(2) / 2, sqrt(2) / 2).
Now, consider the unconstrained maximization problem on the variables
x, y and lambda:
max x + y + lambda * (x^2 + y^2 - 1)
(Notice that the objective fu
onday, March 16, 2009 9:57 pm
Subject: Re: [R] Non-Linear Optimization - Query
To: r-help@r-project.org
> On Tue, Mar 17, 2009 at 12:09 AM, Lars Bishop wrote:
> > I couple of weeks ago, I’ve asked for a package recommendation for
> nonlinear
> > optimization. In my problem I hav
On Tue, Mar 17, 2009 at 12:09 AM, Lars Bishop wrote:
> I couple of weeks ago, I’ve asked for a package recommendation for nonlinear
> optimization. In my problem I have a fairly complicated non-linear objective
> function subject to one non-linear equality constrain.
>
> I’ve been suggested to use
Dear All,
I couple of weeks ago, Ive asked for a package recommendation for nonlinear
optimization. In my problem I have a fairly complicated non-linear objective
function subject to one non-linear equality constrain.
Ive been suggested to use the *Rdonlp2* package, but I did not get any
re
13 matches
Mail list logo
