Re: [R] R optim() function

The issue is almost certainly in the objective function i.e., diagH, since Nelder Mead doesn't use any matrix operations such as Choleski. I think you probably need to adjust the objective function to catch singularities (non-positive definite cases). I do notice that you have two identical

[R] R optim() function

Hi R-Help, I am using R to do functional outlier detection (using PCA to reduce to 2 dimensions - the functional boxplot methodology used in the Rainbow package), and using Hscv.diag function to calculate the bandwidth matrix where this line of code is run: result <- optim(diag(Hstart),

Re: [R] optim with upper and lower bounds

Thanks to all who responded. Will take me some time to digest it all. -Roy > On Aug 11, 2020, at 6:24 AM, J C Nash wrote: > > Thanks to Peter for noting that the numerical derivative part of code doesn't > check bounds in optim(). > I tried to put some checks into Rvmmin and Rcgmin in

Re: [R] optim with upper and lower bounds

Thanks to Peter for noting that the numerical derivative part of code doesn't check bounds in optim(). I tried to put some checks into Rvmmin and Rcgmin in optimx package (they were separate packages before, and still on CRAN), but I'm far from capturing all the places where numerical

Re: [R] optim with upper and lower bounds

This stuff is of course dependent on exactly which optimization problem you have, but optimx::optimr is often a very good drop-in replacement for optim, especially when bounds are involved (e.g., optim has an awkward habit of attempting evaluations outside the domain when numerical derivatives

[R] optim with upper and lower bounds

I am running a lot of optimization problems, at the moment using 'optim' ('optim' is actually called by another program). All of the problems have variables with simple upper and lower bounds, which I can easily transform into a form that is unconstrained and solve using 'BFGS'. But I was

Re: [R] optim function

Subject: Re: [R] optim function Date: Fri, 13 Jul 2018 17:06:56 -0400 From: J C Nash To: Federico Becerra Though I wrote the original codes for 3 of the 5 solvers in optim(), I now suggest using more recent ones, some of which I have packaged. optimx on R-forge (not the one on CRAN yet) has

Re: [R] optim function

There's a CRAN Task View on optimization. There might be something useful there. -Don -- Don MacQueen Lawrence Livermore National Laboratory 7000 East Ave., L-627 Livermore, CA 94550 925-423-1062 Lab cell 925-724-7509 On 7/13/18, 11:43 AM, "R-help on behalf of Federico Becerra" wrote:

[R] optim function

Good afternoon, I am a Biology researcher working on Functional Morphology and Behaviour in mammals. Nowadays, I have a series of morphological data that I would like to test against different models for which I would need to optimize them -namely, "randomly manipulating" all models

Re: [R] Optim function returning always initial value for parameter to be optimized

On 02/10/2018 06:00 AM, r-help-requ...@r-project.org wrote: Did you check the gradient? I don't think so. It's zero, so of course you end up where you start. Try data.input= data.frame(state1 = (1:500), state2 = (201:700) ) err.th.scalar <- function(threshold, data){ state1 <-

Re: [R] Optim function returning always initial value for parameter to be optimized

Did you check the gradient? I don't think so. It's zero, so of course you end up where you start. Try data.input= data.frame(state1 = (1:500), state2 = (201:700) ) err.th.scalar <- function(threshold, data){ state1 <- data$state1 state2 <- data$state2 op1l <- length(state1)

[R] Optim function returning always initial value for parameter to be optimized

Hello, I'm trying to fminimize the following problem: You have a data frame with 2 columns. data.input= data.frame(state1 = (1:500), state2 = (201:700) ) with data that partially overlap in terms of values. I want to minimize the assessment error of each state by using this function:

[R] optim() has a non-consistent way to send parameter for different methods

When optim() is used with method="BFGS", the name of parameters within the vector are transmitted (see below, first example). When method="Brent", the name of parameter (only one parameter can be fitted with Brent method) is not transmitted. As there is only one, of course, we know which

Re: [R] Fwd: Matrix Constraints in R Optim

count <- count+1 >>} >> >>count <-1 >> } >> >> qjk.cal.matrix # RETURN CALCULATED MATRIX TO THE ERROR FUNCTION >> >> } >> >> >> # ERROR FUNCTION - FINDS DIFFERENCE BETWEEN CAL. MATRIX AND ORIGINAL >> MATRIX. Mi

Re: [R] Fwd: Matrix Constraints in R Optim

trix.prod)) >>> >>> count <- 1 >>> number <- 1 >>> for(colnum in 1:ncol(my.data.matrix.prod)) # loop through all >PROD >>> wells columns >>> { >>>sum <-0 >>>for(row in 1:nrow(my.data.matrix.prod)

Re: [R] Fwd: Matrix Constraints in R Optim

1,1,1,1,Inf,1,1,1,1,1,Inf,1,1,1,1,1), lower=c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0)) sols On 17 June 2016 at 16:55, Jeff Newmiller <jdnew...@dcn.davis.ca.us> wrote: Your code is corrupt because you failed to send your email in plain text format. You also don't appear to have

Re: [R] Fwd: Matrix Constraints in R Optim

> the dput function to generate R code form of a sample of your data. > -- > Sent from my phone. Please excuse my brevity. > > On June 17, 2016 1:07:21 PM PDT, Priyank Dwivedi <dpriyan...@gmail.com> > wrote: >> >> By mistake, I sent it earlier to the wrong a

Re: [R] Fwd: Matrix Constraints in R Optim

t; >> Your code is corrupt because you failed to send your email in plain >text format. >> >> You also don't appear to have all data needed to reproduce the >problem. Use the dput function to generate R code form of a sample of >your data. >> -- >> Sent from my ph

Re: [R] Fwd: Matrix Constraints in R Optim

1:07:21 PM PDT, Priyank Dwivedi <dpriyan...@gmail.com> wrote: >By mistake, I sent it earlier to the wrong address. > >-- Forwarded message -- >From: Priyank Dwivedi <dpriyan...@gmail.com> >Date: 17 June 2016 at 14:50 >Subject: Matrix Constraints

[R] Fwd: Matrix Constraints in R Optim

By mistake, I sent it earlier to the wrong address. -- Forwarded message -- From: Priyank Dwivedi <dpriyan...@gmail.com> Date: 17 June 2016 at 14:50 Subject: Matrix Constraints in R Optim To: r-help-ow...@r-project.org Hi, Below is the code snippet I wrote in R: The basi

[R] Optim():Error in solve.default(crossprod(hm, xm), crossprod(hm, ym))

Dear members; I am stuck trying to find optimal parameters using optim() function. I would be veryy gateful if you could help me on this: I have the following equation: Rp,t+1 = rf+ beta*rt+1 (1) Rp,t+1= the return of the portfolio , fr = free risk rate

Re: [R] Optim() and Instability

Since some questioned the scaling idea, here are runs first with scaling and then without scaling. Note how much better the solution is in the first run (see arrows). It is also evident from the data > head(data, 3) y x1 x2 x3 1 0.660 20 7.0 1680 2 0.165 5 1.7 350 3 0.660 20 7.0

Re: [R] Optim() and Instability

> On 14 Nov 2015, at 16:15, Lorenzo Isella wrote: > > Dear All, > I am using optim() for a relatively simple task: a linear model where > instead of minimizing the sum of the squared errors, I minimize the sum > of the squared relative errors. > However, I notice that

[R] Optim() and Instability

Dear All, I am using optim() for a relatively simple task: a linear model where instead of minimizing the sum of the squared errors, I minimize the sum of the squared relative errors. However, I notice that the default algorithm is very sensitive to the choice of the initial fit parameters,

Re: [R] Optim() and Instability

Tyipcally the parameters being optimized should be the same order of magnitude or else you can expect numerical problems. That is what the fnscale control parameter is for. On Sat, Nov 14, 2015 at 10:15 AM, Lorenzo Isella wrote: > Dear All, > I am using optim() for a

Re: [R] Optim() and Instability

I meant the parscale parameter. On Sat, Nov 14, 2015 at 10:30 AM, Gabor Grothendieck wrote: > Tyipcally the parameters being optimized should be the same order of > magnitude or else you can expect numerical problems. That is what the > fnscale control parameter is for.

Re: [R] Optim() and Instability

> On 14 Nov 2015, at 17:02, Berend Hasselman wrote: > >> >> On 14 Nov 2015, at 16:15, Lorenzo Isella wrote: >> >> Dear All, >> I am using optim() for a relatively simple task: a linear model where >> instead of minimizing the sum of the squared

[R] optim for maximization

Hi Sir, How to use the optim for maximization. I don't understand the control$fnscale option that is given on help page. It says if the control$fnscale is negative, the function will be maximized. Thanks a lot Padmanand -- Padmanand Madhavan Nambiar Alternate e-mail id : an...@uga.edu

Re: [R] optim for maximization

Padmanand Madhavan Nambiar padmanandm at gmail.com writes: Hi Sir, How to use the optim for maximization. I don't understand the control$fnscale option that is given on help page. It says if the control$fnscale is negative, the function will be maximized. Thanks a lot Padmanand

Re: [R] optim, L-BFGS-B | constrained bounds on parms?

Evan Cooch evan.cooch at gmail.com writes: You could also use Rvmmin that has bounds, or nmkb from dfoptim (though you cannot start on bounds). One 'negative' for dfoptim is that is doesn't automatically generate the Hessian (as far as I can tell). Rather nice to be able to do so

[R] optim, L-BFGS-B | constrained bounds on parms?

Or, something to that effect. Following is an example of what I'm working with basic ABO blood type ML estimation from observed type (phenotypic) frequencies. First, I generate a log-likelihood function. mu[1] - mu[2] are allele freqs for A and B alleles, respectively. Since freq of O allele

[R] optim, L-BFGS-B | constrained bounds on parms?

on bounds). Best, JN On 14-09-19 06:00 AM, r-help-requ...@r-project.org wrote: Message: 27 Date: Fri, 19 Sep 2014 00:55:04 -0400 From: Evan Cooch evan.co...@gmail.com To: r-help@r-project.org Subject: [R] optim, L-BFGS-B | constrained bounds on parms? Message-ID: 541bb728.6030...@gmail.com Content

Re: [R] optim, L-BFGS-B | constrained bounds on parms?

On 9/19/2014 11:32 AM, Prof J C Nash (U30A) wrote: One choice is to add a penalty to the objective to enforce the constraint(s) along with bounds to keep the parameters from going wild. This generally works reasonably well. Sometimes it helps to run just a few iterations with a big penalty

Re: [R] optim, L-BFGS-B | constrained bounds on parms?

You could also use Rvmmin that has bounds, or nmkb from dfoptim (though you cannot start on bounds). One 'negative' for dfoptim is that is doesn't automatically generate the Hessian (as far as I can tell). Rather nice to be able to do so for other calculations that usual follow after the

[R] Optim function collectively for all Rows in a dataframe

Hello, In the following code, I need to calculate parameters par_1,par_2,par_3,seperately for all the rows in casted data-frame . how may I avoid the for loop because it is taking too much time , as in I want to calculate optimized parameters(initial values 0.2,0.25,0.3 ,,, so that I get

Re: [R] Optim function Hessian matrix

On Nov 19, 2013, at 12:09 PM, sofeira taajobian wrote: Dear R Users Hi, I have very emergency problems in my programming about finding MLE with optim command. I reproduced it with real data. I guess that my function object in optim is very sensitive because it has power function .

Re: [R] Optim function Hessian matrix

This is the code that was attached. I arrived in the copy sent to my email address: #-- L1=function(X){ B1=X[1] C1=X[2] B2=X[3] C2=X[4] mu=X[5] S=-(B1*(C1^x)*((C1^v)-1)/log(C1)) +(d2*log(B1*(C1^(x+v -(B2*(C2^y)*((C2^v)-1)/log(C2)) +(d1*log(B2*(C2^(y+v -(v*mu)

[R] optim evils

Greetings, In obedient deference to the demands of the collective I emailed a BUG report containing code and data to r-b...@r-project.org but found subsequently that I am unable to load the page http://bugs.r-project.org/ to check on the status of this report. Can anyone else load this page?

Re: [R] optim evils

On 02/10/2013 9:18 AM, Michael Meyer wrote: Greetings, In obedient deference to the demands of the collective I emailed a BUG report containing code and data to r-b...@r-project.org but found subsequently that I am unable to load the page http://bugs.r-project.org/ to check on the status of

[R] optim evils

Thanks for all replies. The problem occurred in the following context: A Gaussian one dimensional mixture (number of constituents, locations, variances all unknown) is to be fitted to data (as starting value to or in lieu of mixtools). A likelihood maximization is performed. I'll try to

Re: [R] optim evils

Thanks for all replies. The problem occurred in the following context: A Gaussian one dimensional mixture (number of constituents, locations, variances all unknown) is to be fitted to data (as starting value to or in lieu of mixtools). A likelihood maximization is performed. Cool. That

Re: [R] optim evils

Slight correction: On Thu, Sep 5, 2013 at 7:48 AM, Bert Gunter bgun...@gene.com wrote: Michael: Your parameter specification is probably over-determined, so that you have an infinite set of parameter **values** that give essentially the same solution within numerical error. I would

Re: [R] optim evils

Michael: Your parameter specification is probably over-determined, so that you have an infinite set of parameters that give essentially the same solution within numerical error. I would venture to guess that this will not be fixable with alternative optimizers. It is up to you to provide a

[R] optim evils

It would take some effort to extract selfcontained code from the mass of code wherein this optimization is embedded. Moreover I would have to obtain permission from my employer to do so. This is not efficient. However some things are evident from the trace log which I have submitted: (a)

Re: [R] optim evils

Hi Michael, You do not need to create a self-contained example from the mass of code where it is embedded, but given that optim() works in many cases, to file a bug report, you do need to give _an_ example where it is failing. Here is an example where it works great: optim(1, fn = function(x)

Re: [R] optim evils

-boun...@r-project.org] On Behalf Of Michael Meyer Sent: Wednesday, September 04, 2013 1:35 AM To: r-help@r-project.org Subject: [R] optim evils It would take some effort to extract selfcontained code from the mass of code wherein this optimization is embedded. Moreover I would have

[R] optim evils

package through other packages (bobyqa, nmkb, Rvmmin, Rcgmin) JN On 13-09-04 06:00 AM, r-help-requ...@r-project.org wrote: Message: 67 Date: Wed, 4 Sep 2013 16:34:54 +0800 (SGT) From: Michael Meyerspyqqq...@yahoo.com To:r-help@r-project.org r-help@r-project.org Subject: [R] optim evils

[R] optim evils

Greetings, I am in great anguish as the routine stats::optim shows unexplicable behaviour of various sorts. For one it is immune to the choice of optimization method and seems to always do the same. The following trace log N = 21, M = 5 machine precision = 2.22045e-16 At X0, 0 variables are

Re: [R] optim evils

I don't think anyone can do much to help you unless you show us (a) your objective function OF and your starting value for pars --- which I do not see in your posting. Examples should be ***reproducible***!!! My personal experience with optim() has always been very good. cheers,

Re: [R] [optim/bbmle] function returns NA

Carlos, There are likely several problems with your likelihood. You should check it carefully first before you do any optimization. It seems to me that you have box constraints on the parameters. They way you are enforcing them is not correct. I would prefer to use an optimization algorithm

[R] [optim/bbmle] function returns NA at ... distance from x

Dear R helpers, I try to find the model parameters using mle2 (bbmle package). As I try to optimize the likelihood function the following error message occurs: Error in grad.default(objectivefunction, coef) : function returns NA at

Re: [R] [optim/bbmle] function returns NA at

: [R] [optim/bbmle] function returns NA at ... distance from x Message-ID: CAP=bvwpxj991fbyt9ou5x1jf9nol3vtq1svtjvw82jwfjyz...@mail.gmail.com Content-Type: text/plain Dear R helpers, I try to find the model parameters using mle2 (bbmle package). As I try to optimize the likelihood function

[R] optim with(out) box constraints!

Hello  R users, Does optimizing a function using optim with  method= L-BFGS-B and without box constraints lead to L-BFGS optimization in R?  [[alternative HTML version deleted]] __ R-help@r-project.org mailing list

Re: [R] optim with(out) box constraints!

On 02.08.2013 10:10, Anera Salucci wrote: Hello R users, Does optimizing a function using optim with method= L-BFGS-B and without box constraints lead to L-BFGS optimization in R? Sort of, but the question is why this would be beneficial with today's computers ... Best, Uwe Ligges

Re: [R] optim with(out) box constraints!

, and possibly some other routines. JN On 13-08-02 06:00 AM, r-help-requ...@r-project.org wrote: Message: 36 Date: Fri, 02 Aug 2013 10:38:51 +0200 From: Uwe Liggeslig...@statistik.tu-dortmund.de To: Anera Saluccia.salu...@yahoo.com Cc:r-help@r-project.org r-help@r-project.org Subject: Re: [R] optim

[R] optim() over bogus parameters

Hello, I'm optimizing a log-likelihood function using the built-in optim() function with the default method. The model is essentially a Weibull distribution where the rate parameter changes based on a single covariate, coded 1 or 0 (that is, when the indicator is 1, the rate parameter changes to

Re: [R] Optim seems not to work properly in foreach

Hi Ilai, after you sent this message I tried your code as well and it worked. As a result, I reconsidered the code written by me and of course also found the error in my function simulateEKOP. So for other people assuming errors or ill behavior in base functions: Forget it: these functions are

[R] Optim seems not to work properly in foreach

Hi guys, I am working now for several years in R and I would say I manage things pretty easily, but with the foreach loop I have my problems. I call for a simulation a double foreach loop and this works fine. Inside the second loop (which I plan to parallelize later on) I call Rs

Re: [R] Optim seems not to work properly in foreach

On Mon, Jun 3, 2013 at 11:37 AM, Simon Zehnder szehn...@uni-bonn.de ... [Some not minimal, self contained, reproducible code]... Data simulation and thecreation of startpar works fine, but the parameters in res$par are always the start parameters. If I run the same commands directly on the

Re: [R] optim hangs without warnings or error

Katja, this seems to be a bug. I can reproduce this under 64-bit R-2.15.3 / R-prerelease for Windows. It works with the results given by Ben Bolker under 32-bit R for Windows. Will inspect shortly. Best, Uwe On 07.03.2013 21:08, Katja Hebestreit wrote: Hello, optim hangs for some

[R] optim hangs without warnings or error

Hello, optim hangs for some reason when called within the betareg function (from the betareg package). In this special case, the arguments which are passed to optim cause never ending calculations. I uploaded the arguments passed to optim on:

Re: [R] optim hangs without warnings or error

Katja Hebestreit katja.hebestreit at uni-muenster.de writes: Hello, optim hangs for some reason when called within the betareg function (from the betareg package). In this special case, the arguments which are passed to optim cause never ending calculations. I uploaded the arguments

Re: [R] optim .C / Crashing on run

-help@r-project.org Subject: Re: [R] optim .C / Crashing on run Hi, Thanks for your help. Invoking valgrind under R for the test script I attached produces the following crash report; Rscript optim_rhelp.R -d valgrind Nelder-Mead direct search function minimizer function

Re: [R] optim .C / Crashing on run

:20 AM To: Patrick Burns Cc: r-help@r-project.org Subject: Re: [R] optim .C / Crashing on run Hi, Thanks for your help. Invoking valgrind under R for the test script I attached produces the following crash report; Rscript optim_rhelp.R -d valgrind Nelder-Mead direct search

Re: [R] optim .C / Crashing on run

You might also want to try the Nelder-Mead algorithm, nmk(), in the dfoptim package. It is a better algorithm than the Nelder-Mead in optim. It is all R code, so you might be able to modify it to fit your needs. Ravi Ravi Varadhan, Ph.D. Assistant Professor The Center on Aging and Health

Re: [R] optim .C / Crashing on run

That is a symptom of the C/C++ code doing something like using memory beyond the proper range. It's entirely possible to have crashes in some contexts but not others. If you can run the C code under valgrind, that would be the easiest way to find the problem. Pat On 03/11/2012 18:15, Paul

Re: [R] optim .C / Crashing on run

It looks like my attached files didn't go through, so I'll put them in a public Dropbox folder instead; optim_rhelp.tar.gzhttp://dl.dropbox.com/u/1113102/optim_rhelp.tar.gz Thanks, I'll run a compiled binary of the C++ code through Valgrind see what it reports, then perhaps I'll try an Rscript

Re: [R] optim .C / Crashing on run

When invoking R, you can add -d valgrind to run it under valgrind. On 04/11/2012 11:35, Paul Browne wrote: It looks like my attached files didn't go through, so I'll put them in a public Dropbox folder instead; optim_rhelp.tar.gz http://dl.dropbox.com/u/1113102/optim_rhelp.tar.gz Thanks,

Re: [R] optim .C / Crashing on run

Hi, Thanks for your help. Invoking valgrind under R for the test script I attached produces the following crash report; Rscript optim_rhelp.R -d valgrind Nelder-Mead direct search function minimizer function value for initial parameters = 1267.562555 Scaled convergence tolerance is

Re: [R] optim .C / Crashing on run

Running this valgrind command on the test optim_rhelp.R script R -d valgrind --tool=memcheck --leak-check=full --log-file=optim_rhelp.valgrind.log --vanilla optim_rhelp.R yields this report: optim_rhelp.valgrind.loghttp://dl.dropbox.com/u/1113102/optim_rhelp.valgrind.log Ignoring everything

Re: [R] optim .C / Crashing on run

Playing around with alternate optimzers, I've found that both nlminb the nls.lm Levenberg-Marquadt optimizer in minpack.lm both work with my objective function without crashing, and minimize the function as I'd expect them to. Using optim for amoeba sampling would be nice, but I think I'll just

[R] optim .C / Crashing on run

Hello, I am attempting to use optim under the default Nelder-Mead algorithm for model fitting, minimizing a Chi^2 statistic whose value is determined by a .C call to an external shared library compiled from C C++ code. My problem has been that the R session will immediately crash upon starting

Re: [R] optim and nlminb

, I've never seen a query with a short, testable case fail to get an answer very quickly. JN On 10/11/2012 06:00 AM, r-help-requ...@r-project.org wrote: Message: 92 Date: Wed, 10 Oct 2012 13:16:38 -0700 (PDT) From: nserdar snes1...@hotmail.com To: r-help@r-project.org Subject: [R] optim

Re: [R] optim and nlminb

a fortune? On 10/11/2012 9:56 AM, John C Nash wrote: snip Indeed in several years on the list, I've never seen a query with a short, testable case fail to get an answer very quickly. JN -- Spencer Graves, PE, PhD President and Chief Technology Officer Structure Inspection and

Re: [R] optim and nlminb

I have already try optimx but I got this error message. How to solve it. fn is Linn Function has 10 arguments par[ 1 ]: 0 ? 0.5 ? 1 In Bounds par[ 2 ]: 0 ? 0.5 ? 1 In Bounds In Bounds par[ 3 ]: 0 ? 0.5 ? 1 In Bounds In Bounds In Bounds

[R] optim and nlminb

#optim package estimate-optim(init.par,Linn,hessian=TRUE, method=c(L-BFGS-B),control = list(trace=1,abstol=0.001),lower=c(0,0,0,0,-Inf,-Inf,-Inf,-Inf,-Inf,-Inf,-Inf,-Inf,-Inf),upper=c(1,1,1,1,Inf,Inf,Inf,Inf,Inf,Inf,Inf,Inf,Inf)) #nlminb package

[R] Optim()

Hello, I have some problems regarding the function optim. In my simulations I generate negative binomial data and get estimates of the parameter using the likelihood and the package optim. At some point there appears the warning: - non-finite finite-difference value [] I think it occurs, when

Re: [R] Optim()

On Sat, Sep 29, 2012 at 8:17 AM, wasss deichki...@gmx.net wrote: Hello, I have some problems regarding the function optim. In my simulations I generate negative binomial data and get estimates of the parameter using the likelihood and the package optim. At some point there appears the

[R] optim and the function should not advice

Dear R users, I'm using optim to optimize a pretty complicated function. This function takes the parameter vector theta and within its body I use instructions like sigma-theta[a:b]; computations with sigma... out-c() for (i in 1:d){ a-theta[(3*d+i):c] out[i]-evaluation of an expression

Re: [R] optim and the function should not advice

On 20/09/2012 09:24, Gildas Mazo wrote: Dear R users, I'm using optim to optimize a pretty complicated function. This function takes the parameter vector theta and within its body I use instructions like sigma-theta[a:b]; computations with sigma... out-c() for (i in 1:d){ a-theta[(3*d+i):c]

[R] Optim Problem

Hello, I want to estimate the exponential parameter by using optim with the following input, where t contains 40% of the data and q contains 60% of the data within an interval. In implementing the code command for optim i want it to contain both the t and q data so i can obtain the correct

Re: [R] Optim Problem

On 28-08-2012, at 03:12, Christopher Kelvin wrote: Hello, I want to estimate the exponential parameter by using optim with the following input, where t contains 40% of the data and q contains 60% of the data within an interval. In implementing the code command for optim i want it to

Re: [R] optim() for ordered logit model with parallel regression assumption

On Wed, Aug 1, 2012 at 4:34 PM, Xu Jun junx...@gmail.com wrote: Thanks Michael. Now I switched my approach after doing some google. Following are my new codes: ### library(foreign) readin - read.dta(ordfile.dta, convert.factors=FALSE)

Re: [R] optim() for ordered logit model with parallel regression assumption

Thanks Michael. Now I switched my approach after doing some google. Following are my new codes: ### library(foreign) readin - read.dta(ordfile.dta, convert.factors=FALSE) myvars - c(depvar, x1, x2, x3) mydta - readin[myvars] # remove all

Re: [R] optim() for ordered logit model with parallel regression assumption

Disclaimer: I have not followed this thread at all, but only wish to note: 1) Indicator variables are (almost?) never needed in R -- that you are fooling with them suggests that there is probably a better approach. 2) Your bols is just least regression, no? -- If so, there are far better ways to

Re: [R] optim() for ordered logit model with parallel regression assumption

I am not that proficient in R. I found some codes on web using those indicator variables to sum up log likelihood. I block out bols in the codes, but I also tried using them as start value for my estimation of ologit. Didn't work. Thanks for your suggestion. Jun On Wed, Aug 1, 2012 at 5:44 PM,

[R] optim() for ordered logit model with parallel regression assumption

Dear R listers, I am learning the MLE utility optim() in R to program ordered logit models just as an exercise. See below I have three independent variables, x1, x2, and x3. Y is coded as ordinal from 1 to 4. Y is not yet a factor variable here. The ordered logit model satisfies the parallel

Re: [R] optim() for ordered logit model with parallel regression assumption

On Tue, Jul 31, 2012 at 7:57 PM, Xu Jun junx...@gmail.com wrote: Dear R listers, I am learning the MLE utility optim() in R to program ordered logit models just as an exercise. See below I have three independent variables, x1, x2, and x3. Y is coded as ordinal from 1 to 4. Y is not yet a

[R] optim question

and change. Best, JN Message: 4 Date: Tue, 8 May 2012 14:35:10 -0500 From: Wenhao Gui guiwen...@gmail.com To: r-help@r-project.org Subject: [R] optim question Message-ID: CABZdO=zKr1wsXmTOQ54UieVQfpkAx=cyt0dzip7yt1cjb6e...@mail.gmail.com Content-Type: text/plain Hello, I used optim

[R] optim question

Hello, I used optim to find the MLE estimates of some parameters. See the code below. It works for data1(x). but It did not work for data2 and the error says L-BFGS-B needs finite values of 'fn' . data2: c(x, 32) that is, if I added the number 32 at the end of data1. The error appears

Re: [R] Optim (fct): Parameters=LowerBounds

as saw a log. JN On 05/01/2012 06:00 AM, r-help-requ...@r-project.org wrote: Message: 54 Date: Mon, 30 Apr 2012 08:30:24 -0700 (PDT) From: barb mainze...@hotmail.com To: r-help@r-project.org Subject: [R] Optim (fct): Parameters=LowerBounds!? Message-ID: 1335799824557-4598504.p...@n4.nabble.com

[R] Optim (fct): Parameters=LowerBounds!?

Hey, i am trying to do the MLE for Garch and have a problem with the optim function. Initally i tried optim with Method=BFGS. Reading trhough the forum i found out i would neet bounds. So i went on with Method=L-BFGS-B. But now my parameters equal the lower bounds. out - optim(par=initial,

Re: [R] Optim() package restriction

On Fri, Feb 24, 2012 at 4:03 PM, nserdar snes1...@hotmail.com wrote: I did it like above  but got an error message. estimate- optim(init.par,Linn,gr=NULL,method= L-BFGS-B, hessian=FALSE,control = list(trace=1),lower=c(0,-Inf,Inf,Inf),upper=c(1,Inf,Inf,Inf)) Your lower bound for parameters

[R] Optim() package restriction

Hi I need a phi restriction in my code. That is 0phi1 How can I do that ? Linn=function(param){ phi=param[1] sigw=param[2] sigv=param[3] Betam=param[4] kf=kfilter1(n,st[,k],st[,1],0,1,phi,Betam,sigw,sigv) return(kf$like) } init.par-c(1,1,1,1) estimate-

Re: [R] Optim() package restriction

On Fri, Feb 24, 2012 at 12:18 PM, nserdar snes1...@hotmail.com wrote: Hi I need a phi restriction in my code. That is   0phi1 How can I do that ? init.par-c(1,1,1,1) estimate- optim(init.par,Linn,gr=NULL,method= BFGS, hessian=FALSE,control = list(trace=1)) You want method L-BFGS-B not

Re: [R] Optim() package restriction

Thanks for your attention. I searched this function but I can not find special example about box constraint. Can you give an example for my code? Regards, Ser -- View this message in context: http://r.789695.n4.nabble.com/Optim-package-restriction-tp4418379p4418858.html Sent from the R help

Re: [R] Optim() package restriction

I did it like above but got an error message. estimate- optim(init.par,Linn,gr=NULL,method= L-BFGS-B, hessian=FALSE,control = list(trace=1),lower=c(0,-Inf,Inf,Inf),upper=c(1,Inf,Inf,Inf)) Error in solve.default(sig[, , 1]) : system is computationally singular: reciprocal condition number =

[R] Optim() maximum number of parameters

Hello, I'm trying to maximize a likelihood function for a HMM with the optim() function using the Nelder-Mead Method. The LLF has 20 Parameters which are to be estimated. We found out that R changes some variables but not all of them, especially the last 2 parameters aren't changed. I already

[R] optim - Self-Start values - growth function

Dear community, I'm trying to model growth with this function: Yi = A* exp(-k*(1/ti^m)) ; A asymptote, k rate of decrease of the relative growth rate, m shape parameter. I don't have variable time so, finally, following some papers, I try to fit Yi+a = A*exp(-k*

[R] optim with simulated annealing SANN for combinatorial optimization

, for effective use they require more knowledge than many of their users possess, and can be dangerous because they seem to work. JN Message: 72 Date: Fri, 16 Dec 2011 18:41:12 +1100 From: Dae-Jin Lee lee.dae...@gmail.com To: r-help@r-project.org Subject: [R] optim with simulated annealing SANN

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