similar to: Curve fit a nonlinear equation with box constraints: success, many thanks!

After a few days of work, I think I nearly have it. Unfortunately, theta is unchanged after I run this (as a script from a file). I thought that theta would contain the fitted parameters. The goal here is to find the least squares fit according to the function defined as "rss" subject to the constraints defined as ui and ci. I defined ui and ci to (hopefully) force par2 and par3

Hi, I wonder how to pass several functions and their arguments as arguments to a function. For example, the main function is f = function(X ) { process1(X) ... process2(X) } I have a few functions that operate on X, e.g. g1(X, par1), g2(X, par2), g3(X, par3). par1, par2 and par3 are parameters and of different types. I would like to pass g1, g2, g3 and their arguments to f and g1,

Hi, I wonder how to pass several functions and their arguments as arguments to a function. For example, the main function is f = function(X ) { process(X) ... process(X) } I have a few functions that operate on X, e.g. g1(X, par1), g2(X, par2), g3(X, par3). par1, par2 and par3 are parameters and of different types.

Hi, I am currently working with the sem package in R, to create pathway diagrams. Id like to use the standardized path coeffcients. To get these, I use std.coef. However, using this yields only the standardized coefficients, but does not give me the standard error. Does someone know how to get std.coef to show the standard error of the standardized path coefficients as well? Thanks, Bastiaan

Dear all, Using: library(vegan) data(BCI) mod <- radfit(BCI[1,]) mod RAD models, family poisson No. of species 93, total abundance 448 par1 par2 par3 Deviance AIC BIC Null 39.5261 315.4362 315.4362 Preemption 0.042797 21.8939 299.8041 302.3367 Lognormal 1.0687 1.0186 25.1528 305.0629 310.1281

 Dear R-helpers, I'm a new R-user and I was trying to gain some experience with the GNLS function of the NLME package.  This is an extract from my dataset (it's a 432x6 data.frame) called "input", in the first column I have the values that I need to fit, while the remaining columns are input variables for the theoretical model, the function "mymodel" (which returns a

Dear list, I've recently came across a problem that I think I've solved and that I wanted to share with you for two reasons: - Maybe others come across the same problem. - Maybe someone has a much simpler solution that wants to share with me ;-) The problem is as follows: expand.grid() allows you to generate a data.frame with all combinations of a set of values, e.g.: >

I would like to limit the significant figures of the calibrated parameters determined by genoud() in the Rgenoud package. Below is some example output, where column 1 is model run number, columns 2-7 are the parameter values, and columns 8-12 are model fit statistics. I would like genoud to internally limit parameters to 4 decimal places as shown in this output. It is clear that the function is

Hello! I am getting the following errors when running optim() [I tried optim() with 3 different methods as you can see]: Error in optim(c(0.66, 0.999, 0.064), pe, NULL, method = "L-BFGS-B") : objective function in optim evaluates to length 6 not 1 > out <- optim( c(0.66, 0.999, 0.064), pe, NULL, method = "Nelder-Mead") Error in optim(c(0.66, 0.999, 0.064),

width <- 7 height <- 5 # create whatever device type # and have cex=1 before setting par(mai=) windows(width=width, height=height, rescale="R") oldmai <- par("mai") par(cex=1) par(mai=oldmai) plot.new() par(usr=c(0,2,0,2)) par(cex=2) par1 <- par() text(1,1,"there is hardly anything i know for sure\nneither of the future nor of the past\nnor should i know what

Hi, I have a data frame DATA, which (simplified of course) looks like this: know1 = c("Y","N","N","Y","N","N","Y","Y","N") par1=c(1,4,5,3,3,2,3,3,5) know2 = c("Y","Y","N","Y","N","N","N","Y","Y")

Hi, I have downloaded a R script from http://www.wessa.net/rwasp_edauni.wasp#output. This script produces a densityplot graphic, amongst others, when is executed from the web page. However, when I run it in my machine the *densityplot* function produces any output, I mean a blank graphic. But, it's interesting if I run the following lines in the R interactive console: > y <-

Hello, unfortunately, I don't know a better subject. I would like to be very flexible in how to process my data. Assume the following dataset: par1 <- seq(0,1,length.out = 100) par2 <- seq(1,100) fac1 <- factor(rep(c("group1", "group2"), each = 50)) fac2 <- factor(rep(c("group3", "group4", "group5", "group6"), each =

Dear R users: I have a problem about catch the value from function. I have following two functions (part): sbolus1 <- function() { ....... for( i in 1:Subject) { kel<-par1 Vd<-par2 PKindex<-sbolus1.out(PKtime,kel,Vd,defun,par1,par2,Dose,i) } savefile(PKindex) } sbolus1.out<-function(PKtime,kel,Vd,defun,par1,par2,Dose,i) { time<-PKtime$time

Dear R users, I am a new R user and have some difficulty understanding the functioning of “outer”, where my question is from. I have read the posts related to the questions on the outer function, but unfortunately could not figure out where my mistake is. I have a function with two variables and three parameters (a density function that is not standard) and I want to draw the contourplot along

Hi R users: I'm trying to make a function where two of the parameters are functions, but I don't know how to put each set of parameters for each function. What am I missing? I try this code: f2<-function(n=2,nsim=100,fun1=rnorm,par1=list(),fun2=rnorm,par2=list()){ force(fun1) force(fun2) force(n) p1<-unlist(par1) p2<-unlist(par2) force(p1) force(p2)

Hi R-devel, I am facing a situation where the number of options I would like to propose to the user is somewhat big (and could easily increase more and more as I will code up a little more - even coming to a point where an user should be able to implement his own options). What we have to handle options is the couple: options(par=value) and getOption("par") I was aking myselft what

Dear all, I'm calling Winbugs (1.4.3) through R2WinBugs (2.1-18 coda_0.14-7) to fit a switching random walk model, but come up with an instant trap with the log only displaying 'check('. I will paste the trap with session info below; I'd be very grateful for any ideas. Couple of leads: 1. I presume the problem relates to the r package itself or the way I call bugs(), because I

> From: "Dr. Jens Oehlschlägel" <jens.oehlschlaegel@bbdo-interone.de> > Date: Mon, 15 Jan 2001 13:58:00 +0100 > > Dear Prof. Ripley, > > I do not insist that features are bugs, so I stop sending this to r-bugs > and cc r-devel instead > > > I am replying to this from the archive: I did not actually receive a > copy. > > But it is right

I'm trying to use a self-written function with the summaryBy function (doBy package). I have lots of data from Monte Carlo experiments comparing different estimators across different (combinations of) parameter values, similar to the following form: colnames(mydata) <- c("X", "b0", "b1", # parameter combination, corresponding (true) parameter values