[R-sig-ME] heteroscedastic non-linear model with crossed random effects
L.E.Street at sms.ed.ac.uk
Fri Feb 18 21:46:13 CET 2011
I am trying to model the relationship between the leaf area (lai) and
total foliar nitrogen (tfn) in vegetation plots, in order to
understand the sources of variation in tfn across sites and vegetation
lai and tfn was measured on each plot once, 300 plots in total, across 5 sites
and 4 vegetation types.
'Site' is therefore a factor from 1 to 5 and 'veg_type' is a factor
from 1 to 4.
The theoretical relationship between lai and tfn is non-linear, of the form:
tfn = (No/g)*(1- exp(-g*lai))
where No and g are biologically meaningful parameters.
The most appropriate random effects structure for the model (I think)
is to have crossed factors (vegetation types 1 to 4 all occurring at
sites 1 to 5). The data are heteroscedastic with the variance of
residuals increasing with the fitted values of tfn (though not for all
My question is:
Is it possible to incorporate crossed factors in nlme? If so how?
Or, is it possible to incorporate the heteroscedasticity in nlmer? If so how?
I hope I've explained the problem clearly. I can find similar
questions in the archives, but struggling to find a solution to this
Any help much appreciated.
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