Hello,
I posted this question last week and have not heard anything, I am
wondering if anyone had ideas for testing a model relationship?
I am working with a real-time hydrologic modeling system, and I am using
R (R batch script on Linux) to create a non-linear relationship
(exponential) between observed data. I want to extract the non-linear
coefficients (“b” and “m”) if the relationship can be created, if the
relationship cannot be created I will use default “b” and “m”
coefficients. In the R script I some times get an error of singular
gradient matrix (see below). I want to test whether I can create the
relationship (singular gradient causes the script crash) and use the
model extracted coefficients or use default coefficients.
Model in R batch script:
fit.nls <- nls(P~(b*exp(m*Z)), start=list(m=0.015,b=0.017),
control=list(maxiter=200))
Error in nlsModel(formula, mf, start, wts) :
singular gradient matrix at initial parameter estimates
** the initial parameter values are also the default
Specific Questions:
1) Is there a way to test fit.nls (or the data) prior to see if this
error occurs.
2) Would this test be set up as an if statement?
if (fit is good) {proceed model coefficients} else {use default
coefficients}?
Thanks for all your help,
Doug
--
---------------------------------
Douglas M. Hultstrand, MS
Senior Hydrometeorologist
Metstat, Inc. Windsor, Colorado
voice: 970.686.1253
email: dmhul...@metstat.com
web: http://www.metstat.com
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