Weibull<-function(tet1, tet2,x){
1-exp(-exp(tet1+tet2*log10(x)))
}
range(effectdata_without_controls$conc)
# 0.000135696 0.000247044
range(effectdata_without_controls$effect)
# [1] -7.010672 100.240287
nls(effect ~ Weibull(tet1, tet2, conc))
Your Weibull function has a range of
I'm not the author of nlsModel, so would prefer not to tinker with it.
But "singular gradient" is a VERY common problem with nls() that is used
by nlsModel as I understand it. The issue is actually a singular
Jacobian matrix resulting from a rather weak approximation of the
derivatives (a simple f
A few facts (and some opinions):
First fact:
R understands relative paths (as do the other languages you mentioned) (you
have misunderstood R if you think it doesn't)
Second fact:
R interprets relative paths as being relative to its current working directory
Third fact:
To find out R'
Hi
I do not want to dig too deep into your code so only 2 comments.
1.Try to plot your defined functions with starting parameters and with defined
concentration
something like
plot(conc, Weibull(1,1, conc))
2.Try to use conc with different units, something like
conc1 <- conc*1000
Cheers
Pet
Hi
as I wrote I am not an expert in multiple imputation and others are probably
more capable to give you an answer so please keep your emails coppied to the
list.
The error message is straightforward and clear - object has to be of class lm
My wild guess is that you must not use the whole obje
Hello,
It is my first time using R studio and I am facing the error of
"Error in nlsModel(formula, mf, start, wts) :
singular gradient matrix at initial parameter estimates"
when I try to run my script. From what I read online, I understand that the
error might be due to the parameters. However,
Dear Olivier,
you may find the rprojroot package useful, see
https://github.com/r-lib/rprojroot
and a discussion
https://gist.github.com/jennybc/362f52446fe1ebc4c49f#file-2014-10-12_stop-working-directory-insanity-md
Cheers
Am 06.10.2018 um 13:48 schrieb Olivier GIVAUDAN:
Dear R users,
I wou
Dar Jim,
late, but it works now perfectly. I made a little function for
autoscaling elevation data.
https://stackoverflow.com/questions/50606797/plot-in-real-units-mm/52696705#52696705The
(paper-)printer typically also autoscales, which needs to be
deactivated.
Example for a plot with scale i
Dear all,
Thank you for your remarks.
The data under analysis were multiply-imputed using Mice.
To compare the nested models, I used the following R codes by van Buuren:
pool.compare (Model2, Model1, method = c("wald"), data = NULL)
As far as I know the Wald statistic tests the null hypothesis that
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