Displaying 20 results from an estimated 5000 matches similar to: "testing parallelism of does-response curves using nls()"
2011 Aug 09
1
nls, how to determine function?
Hi R help,
I am trying to determine how nls() generates a function based on the
self-starting SSlogis and what the formula for the function would be.
I've scoured the help site, and other literature to try and figure
this out but I still am unsure if I am correct in what I am coming up
with.
**************************************************************************
dat <-
2005 Apr 23
1
start values for nls() that don't yield singular gradients?
I'm trying to fit a Gompertz sigmoid as follows:
x <- c(15, 16, 17, 18, 19) # arbitrary example data here;
y <- c(0.1, 1.8, 2.2, 2.6, 2.9) # actual data is similar
gm <- nls(y ~ a+b*exp(-exp(-c*(x-d))), start=c(a=?, b=?, c=?, d=?))
I have been unable to properly set the starting value '?'s. All of
my guesses yield either a "singular gradient" error if they
2008 Feb 18
2
skip non-converging nls() in a list
Howdee,
My question appears at #6 below:
1. I want to model the growth of each of a large number of individuals using
a 4-parameter logistic growth curve.
2. nlme does not converge with the random structure that I want to use.
3. nlsList does not converge for some individuals.
4. I decided to go around nlsList using:
t(sapply(split(data, list(data$id)),
function(subd){coef(nls(mass ~
2003 Feb 22
2
4-parameter logistic model
Dear R users
I'm a new user of R and I have a basic question about the 4-parameter
logistic model. According to the information from Pinheiro & Bates the model
is:
y(x)=theta1+(theta2-theta1)/(1+exp((theta3-x)/theta4)) ==
y(x)=A+(B-A)/(1+exp((xmid-input)/scal))
from the graph in page 518 of the book of the same authors (mixed models in
S) theta 1 corresponds to the horizontal asymptote
2005 Jun 02
1
nls.control: increasing number of iterations
Hello,
I'm using the nls function and would like to increase the number of
iterations. According to the documentation as well as other postings on
R-help, I've tried to do this using the "control" argument:
nls(y ~ SSfpl(x, A, B, xmid, scal), data=my.data,
control=nls.control(maxiter=200))
but no matter how much I increase "maxiter", I get the following error
2005 May 10
2
predict nlme syntax
Dear all
Please help me with correct syntax of predict.nlme.
I would like to predict from nlme object for new data.
I used predict(fit.nlme6, data=newdata) but I have always got
fitted values, no matter how I changed newdata.
I have
> summary(fit.nlme6)
Nonlinear mixed-effects model fit by maximum likelihood
Model: konverze ~ SSfpl(tepl, A, B, xmid, scal)
Data: limity.gr
AIC
2002 Sep 27
2
How to apply SSfpl with binary data
Dear R-help subscribers
Would you tell me how to apply SSfpl with binary data as below?
Unfortunately, there is not the EXAMPLE in help(SSfpl) for binary data but for quantitative data(Chick).
V1: dose
V2: log-transformed dose
V3: response (rate)
V1 V2 V3
1 0.775 -0.2548922 0.1666667
2 5.000 1.6094379 0.8148148
3 10.000 2.3025851 0.5000000
4 20.000 2.9957323
2005 Nov 13
4
Robust Non-linear Regression
Hi,
I'm trying to use Robust non-linear regression to fit dose response curves.
Maybe I didnt look good enough, but I dind't find robust methods for NON
linear regression implemented in R. A method that looked good to me but is
unfortunately not (yet) implemented in R is described in
http://www.graphpad.com/articles/RobustNonlinearRegression_files/frame.htm
2017 Oct 20
1
Error messages using nonlinear regression function (nls)
Thank you Martin.
If I understand correctly, OP could do
wheat.list <- nlsList(Prop ~ SSfpl(end, A, B, xmid, scal), data=wlg)
or add some small value to all zeroes
wlg$prop < -wlg$Prop+1e-7
wheat.list <- nlsList(prop ~ SSlogis(end,Asym, xmid, scal), data=wlg)
which gives fairly reasonable results.
plot(augPred(wheat.list))
Am I correct?
Cheers
Petr
> -----Original Message-----
2001 May 01
0
SSfpl self-start sometimes fails... workaround proposed
Hello,
nls library provides 6 self-starting models, among them: SSfp, a four
parameters logistic function. Its self-starting procedure involves several
steps. One of these steps is:
pars <- as.vector(coef(nls(y ~ cbind(1, 1/(1 + exp((xmid - x)/exp(lscal)))),
data = xydata, start = list(lscal = 0), algorithm = "plinear")))
which assumes an initial value of lscal equal to 0. If lscal
2017 Oct 20
0
Error messages using nonlinear regression function (nls)
>>>>> PIKAL Petr <petr.pikal at precheza.cz>
>>>>> on Fri, 20 Oct 2017 06:33:36 +0000 writes:
> Hi
> Keep your messages in the list, you increase your chance to get some answer.
> I changed your data to groupedData object (see below), but I did not find any problem in it.
> plot(wlg)
> gives reasonable picture and I am
2017 Jul 11
1
fit lognorm to cdf data
Hi
Great. I did not think that such combination is posssible.
Thanks.
Petr
> -----Original Message-----
> From: peter dalgaard [mailto:pdalgd at gmail.com]
> Sent: Tuesday, July 11, 2017 1:11 AM
> To: PIKAL Petr <petr.pikal at precheza.cz>
> Cc: r-help at r-project.org
> Subject: Re: [R] fit lognorm to cdf data
>
> How about
>
> proc <- c(0.9, 0.84, 0.5,
2017 Jul 10
4
fit lognorm to cdf data
Dear all
I am struggling to fit data which form something like CDF by lognorm.
Here are my data:
proc <- c(0.9, 0.84, 0.5, 0.16, 0.1)
size <- c(0.144, 0.172, 0.272, 0.481, 0.583)
plot(size, proc, xlim=c(0,1), ylim=c(0,1))
fit<-nls(proc~SSfpl(size, 1, 0, xmid, scal), start=list(xmid=0.2, scal=.1))
lines(seq(0,1,.01), predict(fit, newdata=data.frame(sito=seq(0,1,.01))), col=2)
I tried
2017 Jul 10
0
fit lognorm to cdf data
How about
proc <- c(0.9, 0.84, 0.5, 0.16, 0.1)
size <- c(0.144, 0.172, 0.272, 0.481, 0.583)
plot(size, proc, xlim=c(0,1), ylim=c(0,1))
fit<-nls(proc~plnorm(size, log(xmid), sdlog, lower=FALSE), start=list(xmid=0.2, sdlog=.1))
summary(fit)
lines(fitted(fit)~size)
-pd
> On 10 Jul 2017, at 16:27 , PIKAL Petr <petr.pikal at precheza.cz> wrote:
>
> Dear all
>
> I am
2001 Apr 29
1
Self-starting nls functions
Hello,
I am doing several self-starting growth functions for using with nls(). When
I list the self-starting functions included in nls library, for instance,
SSlogis, there is:
> SSlogis
function (input, Asym, xmid, scal)
...
<environment: 03476D20>
attr(,"class")
[1] "selfStart"
What is this <environment: 03476D20> instruction?
By using deriv() and then
2017 Jul 10
0
fit lognorm to cdf data
* fitdistr?
* it seems unusual (to me) to fit directly to the data with lognormal... fitting a normal to the log of the data seems more in keeping with the assumptions associated with that distribution.
--
Sent from my phone. Please excuse my brevity.
On July 10, 2017 7:27:47 AM PDT, PIKAL Petr <petr.pikal at precheza.cz> wrote:
>Dear all
>
>I am struggling to fit data which form
2006 Aug 24
2
my error with augPred
Dear all
I try to refine my nlme models and with partial success. The model is
refined and fitted (using Pinheiro/Bates book as a tutorial) but when
I try to plot
plot(augPred(fit4))
I obtain
Error in predict.nlme(object, value[1:(nrow(value)/nL), , drop =
FALSE], :
Levels (0,3.5],(3.5,5],(5,7],(7,Inf] not allowed for
vykon.fac
>
Is it due to the fact that I have unbalanced
2004 Jul 16
1
Does AIC() applied to a nls() object use the correct number of estimated parameters?
I'm wondering whether AIC scores extracted from nls() objects using
AIC() are based on the correct number of estimated parameters.
Using the example under nls() documentation:
> data( DNase )
> DNase1 <- DNase[ DNase$Run == 1, ]
> ## using a selfStart model
> fm1DNase1 <- nls( density ~ SSlogis( log(conc), Asym, xmid, scal ),
DNase1 )
Using AIC() function:
>
2004 May 06
1
sporadic errors with nlrq() / optim()
Dear List,
Apologies if this is a known problem ... I wasn't able to find it on the bug
list, but it is a problem that does not seem to occur with a MAC build of R
2.0, so perhaps this problem has already been addressed for the future.
I am getting *sporadic* errors when refitting the same model to the same
data set, using nlrq() in the nlrq package. The algorithm is not stochastic,
so I
2008 Feb 19
0
nlsList - Error in !unlist(lapply(coefs, is.null))
Howdee,
I am able to fit a 4-parameter logistic growth curve to a dataset which
comprise many individuals (using R v. 2.3.1). Yet, if I want to obtain the
parameters for each individual (i.e., for each 'id') using nlsList, then I
obtain an Error message which I have trouble interpreting. Any advice as to
how I can solve this problem?
Thanks for your time,
Marc
> reg <-nls(mass ~