I am working with estimates of vegetation height derived from radar data.

We have a nonlinear model to correct these estimates for errors associated

with viewing geometry. I am trying to estimate a single parameter in this

model while accounting for spatial (spherical structure) autocorrelation.

I'd also like to statistically test the influence of several vegetation

parameters. The gnls() function in the nlme library seems well-suited for

fitting this model, but I am having trouble getting it to converge, even

without the autocorrelation structure. Here is the model I'd like to fit:

th=eh*((1+theta/thetaref)/(theta/thetaref))^(1/n), where th=true height

(dependent variable); eh=estimated height (independent variable); theta is

local incidence angle (independent variable); thetaref is fixed; n is the

parameter to be estimated. My question is: is this parameterization

efficient for gnls()? I've gotten reasonable results by changing the

control settings, but also lots of warning messages.

Thanks,

Alan Swanson

[[alternative HTML version deleted]]

______________________________________________

[hidden email] mailing list

https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide!

http://www.R-project.org/posting-guide.html