Dear all, I used modFit of the package FME to fit a set of ODE to a ste of eperiemntal data.
The summary of this fit give me the following error > summary(Fit) Residual standard error: 984.1 on 452 degrees of freedom Error in cov2cor(x$cov.unscaled) : 'V' is not a square numeric matrix In addition: Warning message: In summary.modFit(Fit) : Cannot estimate covariance; system is singular This is due becasue the Hessian matrix has all the entries equal to 0. In these cases, on the help page of modFit, it is suggested to use modMCMC to generate new sets of parameters. modMCMC performs a Markov Chain Monte Carlo simulation. I do not understand very well how modMCMC can be used in a context of parameter estimation. Could someone help me in understanding the use of this function and its utility for parameter fiting? Thank you very much in advance, Paola. -- *Paola Lecca, PhD* *The Microsoft Research - University of Trento* *Centre for Computational and Systems Biology* *Piazza Manci 17 38123 Povo/Trento, Italy* *Phome: +39 0461282843* *Fax: +39 0461282814* [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.