similar to: Multi-objective optimization

Dear All, I am trying to solve the following maximization problem with R: find x(t) (continuous) that maximizes the integral of x(t) with t from 0 to 1, subject to the constraints dx/dt = u, |u| <= 1, x(0) = x(1) = 0. The analytical solution can be obtained easily, but I am trying to understand whether R is able to solve numerically problems like this one. I have tried to find an

Please note clarifications in <<>> below. My apologies for any confusion. Thanks again, Scott ---------- Forwarded message ---------- From: Scott Stark <stark.sc@gmail.com> Date: Aug 23, 2007 1:03 PM Subject: Expedite scalar f(x) evaluation over vectors To: r-help@lists.r-project.org Dear R community, I am trying to code a fairly complex equation for optim(). My current

Hi! I'm translating some code from Matlab to R and I found a problem. I need to translate Matlab's function 'lsqnonlin' (http://www-ccs.ucsd.edu/matlab/toolbox/optim/lsqnonlin.html) into R, and at the beginning I thought it would be the same as R's 'optim'. But then I looked at the definition of 'lsqnonlin' and I don't quite see how to make

I am helping my wife do some statistical analysis. She is a biologist, and she has performed some measurements on various genotypes of mice. My background is in applied mathematics and engineering, and I have a fairly good statistics background, but I am by no means a PhD level expert in statistical methods. We have used the lmer package to fit various models for the various experiments that she

Hi everybody, consider please an optimization problem: minimize sum S1+S2 Subject to : y - x =< A + S1 x - y =< A + S2 and we want to add two more constraints: y - x =< B - S3 x - y =< B - S4 where A is a small constant value and B is a large constant value, S1 and S2 are surplus and S3

I have executed a Repeated Measures ANOVA with one DV (latency) and one within subject factor (acoustic condtion: 3 levels) by bootstrapping my sampling distribution of F from the empirical sample distribution. I chose to resample because the sample distribution deviates from normality a lot. The overall F is significant and now I wish to decompose this with contrasts to ask if latencies to

[Yes, this is related to a homework problem, but is not the problems itself.] In my mathematical statistics class, we've just learned about properties of estimators, and I can now solve manually problems like this: A sample of size n = 16 is drawn from a normal distribution where sigma = 10 but mu is unknown. If mu = 20, what is the probability that the estimator mu hat = Y bar will lie

Dear R help archive group, I am looking for a maximization routine that I can use to maximize a large variety of relatively complex likelihoods. I undertand (from previous posts) that coding the objective function more efficiently can help. However, the optimization routine employed seems important too. So far, I have tried the optimization routines optim, maxlik, trust and nlminb. The latter two

Dear R-Help List, I am using optim, with method=L-BFGS-B, to maximize a likelihood inside a large simulation exercise. This runs fine for most simulated data sets, but for some reason, about 1 out of 100 times, optim will just hang. Using a dumb approach to the problem (i.e. printing the parameter values each time the function being maximized is evaluated), I tracked down when this happens,

I have a server that runs stand-alone with an LDAP directory and a KDC . The linux machines have sssd to allow unified users etc. The clients are mostly MacOS and Windows machines that aren't part of an AD. This config has worked for 15 years, but after upgrading Debian and bringing in Samba Version 4.17.7-Debian it seems to be broken. I believe this is related to:

Folks, I wonder if anything could be said about the distribution of a random variate x, where x = N(0,1)/N(0,1) Obviously x is pathological because it could be 0/0. If we exclude this point, so the set is {x/(0/0)}, does x have a well defined distribution? or does it exist a distribution that approximates x. (The case could be generalized of course to N(mu1, sigma1)/N(mu2, sigma2) and one

I forgot to add that I first gave a starting value for K. Nonlinear least squares won't work because my errors are not normally distributed. Any advide on my maximum likelihood function would be greatly appreciated. ---------------------------- Original Message ---------------------------- Subject: RE: [R] maximum likelihood problem From: "Ravi Varadhan" <rvaradhan at

Hi, New to R, I don't find a way to plot the following data with image(): x is a N * M matrix y is a vector of length M z is a N*M matrix I wish to plot z as a greyscale image, but my x axis is different for every row of the z data. Here is a minimal example, > theta<-c(3:6) # N > y<-c(1:5) # M > > x<-theta%*%t(y)# N * M > z<-sin(x) # N * M > > image(z)

I am a SAS user currently evaluating R as a possible addition or even replacement for SAS. The difficulty I have come across straight away is R's apparent difficulty in handling relatively large data files. Whilst I would not expect it to handle datasets with millions of records, I still really need to be able to work with dataset with 100,000+ records and 100+ variables. Yet, when reading

Hello: I am using R mainly on windows XP, version 2.5. I?m a biologist, with a medium level statistics background. I have a problem stating a two-way factorial design where both factors are random. I?m using the lmer() function implemented in the Matrix package version 0.99. My design is as follows: Two species were randomly selected from a total of 4 species. This species are present

Hi everyone, I am currently using the function optim() to maximize/minimize functions and I would like to see more output of the optimization procedure, in particular the numerical gradient of the parameter vector during each iteration. The documentation of optim() describes that the trace parameter should allow one to trace the progress of the optimization. I use the following command:

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I have 316 files. Each file represents a patient's breathing track (respiratory signal recorded for a variable number of cycles). All files have the same are made up of a header followed by a variable number of records. Each record contains 7 comma separated fields. The patient ID is recorder in the header which is stripped off when reading the file into a R data.frame. Since I need to keep

Dear All, 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 the *Rdonlp2* package, but I did not get any results after running the program for 5 hrs. Is it normal to run this type of programs for hours? Also,

Dear All, I know how to export graphics as pdf files and then how to include them in LaTeX documents. However, I do not know how to do in order to have the text of the graphics written with the font selected for the LaTeX document. Is that possible? Thanks in advance, Paul