[ADMB Users] Log transformation correction
Sylvain Bonhommeau
sylvain.bonhommeau at gmail.com
Fri Aug 23 02:28:22 PDT 2013
Dear group,
To estimate the parameters of a von Bertalanffy model (length <-
(Linf-(Linf-Lo)*exp(k*age))), i log-transform the data and the prediction
of L (L=length). There is however an offset in L_inf estimates and this can
be due to the log-transformation. I try to correct the estimates using a
bias correction method where you multiply the estimates by
10^(Mean_Square_Error/2) but it's seems that it doesn't work. (
http://www.vims.edu/people/newman_mc/pubs/Newman1993.pdf)
Anyway, i have done a simulation framework to generate data of
length-at-age with a small noise (5%) and I boostrap this and estimate the
parameters using ADMB, nls and STAN for comparison purposes. I then
estimates the estimation errors for each bootstrap without correction
(without_corr.pdf). ADMB and STAN are very similar (although STAN is way
longer) while nls is clearly not good. with_corr.pdf is the same with the
correction factor...
Does anyone have an idea how to correct the bias of parameter estimation?
Thanks!
Sylvain
PS: simulation_VB.R is the code to simulate the data and fit the VB
vb.stan is the STAN code
vb_simu.tpl is the ADMB code
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