similar to: non linear 3SLS with constraints

hi all, sorry for this basic question, I think I know I should use ?apply, but it is really confusing me... I want to create a matrix by comparing two vectors. Eg: test<-seq(1:10) fac<-c(3,6,9) and i want to end up with a 10*3 matrix with a boolean that tests if test<fac, so something like: 1 1 1 1 1 1 0 1 1 0 1 1 0 1 1 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 I can't find the solution

Hi all, I made a dotplot() with lattice, which comes out nice on the graphics device. I can save this as a eps using postscript() and include this in a word document. This prints nice, but does not look good on screen. If I produce a pdf, it is nice on screen, but not on paper. How can I save a graph that looks nice on paper and on screen? Bjorn Bjorn Van Campenhout Institute of Development

I am running R on ubuntu dapper. The version that is in the ubuntu repos is 2.2.1, so I decided to upgrade by adding deb http://cran.R-project.org/bin/linux/ubuntu dapper/ to my sources.list, as advised on the web page. After sudo apt-get update and upgrade, I have version 2.3.1. However, when I try to load the library 'foreign', I get the following error: Error in dyn.load(x,

Dear Rexperts, lately I'm having troubles installing the rgl package via install.packages("rgl", dependencies=T) in the R 2.4.0 backport running under Ubuntu 6.06 LTS. I get the following error messages, despite having installed libx11-dev (as recommended in a similar post about SUSE 10.1): trying URL 'http://cran.xedio.de/src/contrib/rgl_0.68.tar.gz' Content type

Function DEoptim in package DEoptim for differential evolution defines an optional parameter fnMap: fnMap "an optional function that will be run after each population is created, but before the population is passed to the objective function. This allows the user to impose integer/cardinality constriants." Unfortunately, there is no further documentation decribing the kind of

I'd like to be able to test linear hypotheses after setting up and running a model using optim or perhaps nlm. One hypothesis I need to test are that the average of several coefficients is less than zero, so I don't believe I can use the likelihood ratio test. I can't seem to find a provision anywhere for testing linear combinations of coefficients after max. likelihood. Cheers

I am using nlsLM {minpack.lm} to find the values of parameters a and b of function myfun which give the best fit for the data set, mydata. mydata=data.frame(x=c(0,5,9,13,17,20),y = c(0,11,20,29,38,45)) myfun=function(a,b,r,t){ prd=a*b*(1-exp(-b*r*t)) return(prd)} and using nlsLM myfit=nlsLM(y~myfun(a,b,r=2,t=x),data=mydata,start=list(a=2000,b=0.05), lower = c(1000,0),

> On Jun 18, 2017, at 6:24 AM, Manoranjan Muthusamy <ranjanmano167 at gmail.com> wrote: > > I am using nlsLM {minpack.lm} to find the values of parameters a and b of > function myfun which give the best fit for the data set, mydata. > > mydata=data.frame(x=c(0,5,9,13,17,20),y = c(0,11,20,29,38,45)) > > myfun=function(a,b,r,t){ > prd=a*b*(1-exp(-b*r*t)) >

Greetings, I am interested in using a generalized linear mixed model with data that best fits a beta distribution (i.e., the data is bounded between 0 and 1 but is not binomial). I noticed that the beta distribution is not listed as an option in the "family objects" for glmmPQL or lmer. I found a thread on this listserve from 2006 ("[R] lmer and a response that is a

Hi folks I have some data to which I've been fitting linear mixed effects models. I am currently using a lme model in the nlme package, with terms for random effects due to repeated measures on individuals and the corCAR1 serial correlation structure. However, there is some suggestion in the data (and from theory) that a breakpoint (change point) model may be more appropriate. Scott, Norman

Dear R-Users, I am comparing the nlme package in S-Plus (v. 7.0) and R (v. 2.2.1, nlme package version 3.1-68.1; the lattice, Matrix, and lme4 have also just been updated today, Jan. 23, 2006) on a PC (2.40 GHz Pentium 4 processor and 1 GHz RAM) operating on Windows XP. I am using a real data set with 1,191 units with at most 4 repeated measures per unit (data are incomplete, unbalanced). I

Thanks to Gabor, Duncan, and Peter. I knew the answer had something to do with solving for a and b in terms of mean and variance. I will build a function using the equations you provided Duncan and will look into using Mathomatic in the future Gabor. Appreciate the help. Peter, this was not homework but I understand your concern. I don't use listserves that often but they do open a whole

Hello, I'm working on the multiple categorical data (5-points scale) using linear mixed effect model and wondering if anyone knows about or works on the linear mixed effect model with ordered logit or probit link. I found that the "lmer" function in R is very flexible and supports various models, but not ordered logit/probit models. I may conduct my analysis by turning my DVs

I ran the following script. I satisfied the constraint by making a*b a single parameter, which isn't always possible. I also ran nlxb() from nlsr package, and this gives singular values of the Jacobian. In the unconstrained case, the svs are pretty awful, and I wouldn't trust the results as a model, though the minimum is probably OK. The constrained result has a much larger sum of squares.

Hello! I am running R-2.3.1-i386-1 on Slackware Linux 10.2. I am a former matlab user, moving to R. In matlab, via the cftool, I performed nonlinear curve fitting using the method "nonlinear least squares" with the "Trust-Region" algorithm and not using robust fitting. Is it possible to perform the same analysis in R? I read quite a lot of R documentation, but I could not find

https://cran.r-project.org/web/views/Optimization.html (Cran's optimization task view -- as always, you should search before posting) In general, nonlinear optimization with nonlinear constraints is hard, and the strategy used here (multiplying by a*b < 1000) may not work -- it introduces a discontinuity into the objective function, so gradient based methods may in particular be

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,

We have been running Asterisk for about a month now and one of the things I miss the most is the ability to se who's online and available and who's not. Surely, there's the manager interface, but unless you'd want to install extra software on each client computer, this is not a good option. Then there's the presence / IM function in SIP. Since we're only using SIP

Hi I would like to know how to pivot a table that will sum the number of plants (a or b) for each location (x,y,z) I have read on the listserve similar questions but which involve summing up numbers rather than factors. I have also read about the R package reshape on the listserve but wanted to know if there's a way to do it easily without the package Thanks for the help! location plant x

Hello, I want to solve a nonlinear 3SLS problem with "nlsystemfit()". The equations are of the form y_it = f_i(x,t,theta) The functions f_i(.) have to be formulated as R-functions. When invoking "nlsystemfit()" I get the error Error in deriv.formula(eqns[[i]], names(parmnames)) : Function 'f1' is not in the derivatives table