Re: [R] Fitting data with optim or nls--different time scales

From: Spencer Graves <>
Date: Thu 10 Aug 2006 - 18:40:59 EST

<see in line>

Leslie Chavez wrote:
> Hi,
> I have a system of ODE's I can solve with lsoda.
> Model=function(t,x,parms)
> {
> #parameter definitions
> lambda=parms[1]; beta=parms[2];
> d = parms[3]; delta = parms[4];
> p=parms[5]; c=parms[6]
> xdot[1] = lambda - (d*x[1])- (beta*x[3]*x[1])
> xdot[2] = (beta*x[3]*x[1]) - (delta*x[2])
> xdot[3] = (p*x[2]) - (c*x[3])
> return(list(xdot))
> }
> I want to fit the output out[,4] to experimental data that is only
> available on days 0, 7, 12, 14, 17, and 20. I don't know how to set up
> optim or nls so that it takes out[,4] on the appropriate day, but still
> runs lsoda on a time scale of 0.01 day.
> Below is the function I've been using to run 'optim', at the
> course-grained time scale:
SG: What about the following:

  Modelfit=function(s) {

	lsodaTimes <- seq(min(times),max(times), by=0.01)
	obsTimes <- (100*times-1)
  #	cat(times)


          Your example is not self contained, so obviously I haven't tried this with it. However, something of this nature should work fine, I believe.   Something similar but different should also work, I believe, with 'nls'; this would give you access to many helper functions (see "methods(class='nls')"). If 'nls' bombed on me, I'd then try 'optim' as it is less brittle. Then I might use the output of 'optim' as initial values for 'nls' to get confidence intervals etc.

	  hope this helps.
	  Spencer Graves

> #x0=c(T0,I0,V0)
> x0=c(2249,0,1)
> #parms(lambda, beta, d, delta, p, c)
> parms[5:6]=c(1.0,23)
> s0=c(49994,8456,6.16E-8,0.012) #initial values
> fit=optim(s0,Modelfit)
> Right now, lsoda is being run on too course-grained a time scale in the
> function Modelfit. Most examples of optim and nls I have found compare
> two data sets at the same times, and run lsoda on the time scale the
> data is available at, but I would like to run lsoda at a finer scale, and
> only compare the appropriate time points with the experiment. I have also
> tried using nls, but I have the same problem. Does anyone have
> suggestions?
> Thank you very much,
> Leslie
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> and provide commented, minimal, self-contained, reproducible code. mailing list PLEASE do read the posting guide and provide commented, minimal, self-contained, reproducible code. Received on Thu Aug 10 19:55:28 2006

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