Displaying 2 results from an estimated 2 matches for "pourcma".
2009 Mar 27
3
nls, convergence and starting values
...model. This has worked OK for almost all the other data sets except
that one (dumped below). Whatever our trials and algorithms, even
subsetting data (to check if some singular point was the cause of the
mess), we do not reach convergence... or screw up with singular
gradients (?) etc...
eg:
nls(pourcma~SSlogis(transat, Asym, xmid, scal), start=c(Asym=30,
xmid=0.07, scal=0.02),data=bdd, weights=sqrt(nbfeces),trace=T,alg="plinear")
As anyone a hint about an alternate approach to fit a model ? Or an idea
to get evidence that such model cannot be fitted to the data....
bdd <-
structur...
2009 Apr 01
0
回复： R-help Digest, Vol 73, Issue 32
...alculation of
starting values and relatively robust optimization, which can be used with success in many
common cases of nonlinear regression, also for your data:
library(drc) # on CRAN
## Fitting 3-parameter logistic model
## (slightly different parameterization from SSlogis())
bdd.m1 <- drm(pourcma~transat, weights=sqrt(nbfeces), data=bdd, fct=L.3())
plot(bdd.m1, broken=TRUE, conLevel=0.0001)
summary(bdd.m1)
Of course, standard errors are huge as the data do not really support this model (as
already pointed out by other replies to this post).
Christian
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