[R-sig-dyn-mod] FME Package -help

[Adriele Giaretta Biase]

       I am working on my thesis, at the University of São Paulo – Brazil,
I am using the delayed rejection and adaptative Metropolis (included in the
FME Package) and Bootstrapping (using the Nelder-Mead algorithm)  to
estimate the best set and parameter distributions for an EDO model and a
very small dataset (n = 27, divided in four groups of n = [4,5,9,9].
Besides, I have estimated the parameters for each individual animal
(minimizing quadratic deviation).

      Although the estimate of parameter values are similar between those
methods, the covariance was extremely different. The parameters have
Gaussian distribution. In the larger groups, the Bootstrap and individual
based covariances estimates seems to converge. However, it is not the case
for the Bayesian.

      Please, could you help me making sure that I am using the FME package
correctly to estimate the Bayesian covariances. Would those differences be
expected? I include the code for your information.


       Thanks in advance,

       Adriele.

-- 
Adriele Giaretta Biase.
Mestre em  Estatística e Experimentação Agropecuária - UFLA.
Doutoranda em Estatística e Experimentação Agronômica - ESALQ/ USP
Contato: (19) 8861-0619.