Re: [R] nls problem with R

2011-05-08 Thread sterlesser
I am sorry,Andrew,I don't get you. Please forgive my poor English. -- View this message in context: http://r.789695.n4.nabble.com/nls-problem-with-R-tp3494454p3508131.html Sent from the R help mailing list archive at Nabble.com. __

Re: [R] nls problem with R

2011-05-08 Thread sterlesser
Thanks Mike. Your suggestion is really helpful.I did with the your instruction , it really works out. What's more,can you use this package http://cran.r-project.org/web/packages/minpack.lm/index.html it use Levenberg-Marquardt algorithm. Can this package do with four parameters? Thanks again --

Re: [R] nls problem with R

2011-05-05 Thread sterlesser
the dataset's form is changed after my post so I repost it here t 0 0.3403 0.4181 0.4986 0.7451 1.0069 1.5535 1.8049 2.4979 6.4903 13.5049 27.5049 41.5049 V(t) 6.053078443 5.56937391 5.45484486 5.193124598 4.31386722 3.645422269 3.587710965 3.740362689 3.699837726 2.908485019 1.888179494

Re: [R] nls problem with R

2011-05-05 Thread sterlesser
ID1 ID2 t V(t) 1 1 0 6.053078443 2 1 0.3403 5.56937391 3 1 0.4181 5.45484486 4 1 0.4986 5.193124598 5 1 0.7451 4.31386722 6 1 1.0069 3.645422269 7 1 1.5535 3.587710965 8

[R] nls problem with R

2011-05-04 Thread sterlesser
the original data are V2 =c(371000,285000 ,156000, 20600, 4420, 3870, 5500 ) T2=c( 0.3403 ,0.4181 ,0.4986 ,0.7451 ,1.0069 ,1.553) nls2=nls(V2~v0*(1-epi+epi*exp(-cl*(T2-t0))),start=list(v0=10^7,epi=0.9,cl=6.2,t0=8.7)) after execution error occurs as below

Re: [R] nls problem with R

2011-05-04 Thread sterlesser
Thanks Ruben. Your suggestion about more deeper analysis about the model itself is really helpful. I am trying out some new initial values based on the analysis of the special T2 in the model. -- View this message in context:

Re: [R] nls problem with R

2011-05-04 Thread sterlesser
Thanks Andrew. I am sorry for some typos that I omit some numbers of T2. Based on your suggestion,I think the problem is in the initial values. And I will read more theory about the non-linear regression. -- View this message in context: