[R] Help with nls and error messages singular gradient
Hi All, I'm trying to run nls on the data from the study by Marske (Biochemical Oxygen Demand Interpretation Using Sum of Squares Surface. M.S. thesis, University of Wisconsin, Madison, 1967) and was reported in Bates and Watts (1988). Data is as follows, (stored as mydata) time bod 11 0.47 22 0.74 33 1.17 44 1.42 55 1.60 67 1.84 79 2.19 8 11 2.17 I then run the following; #Plot initial curve plot(mydata$time, mydata$bod,xlab="Time (in days)",ylab="biochemical oxygen demand (mg/l) ") model <- nls(bod ~ beta1/(1 - exp(beta2*time)), data = mydata, start=list(beta1 = 3, beta2 = -0.1),trace=T) The start values are recommended, (I have used these values in SPSS without any problems, SPSS returns values of Beta1 = 2.4979 and Beta2 = -2.02 456) but return the error message, Error in nls(bod ~ beta1/(1 - exp(beta2 * time)), data = mydata, start = list(beta1 = 3, : singular gradient Can anyone offer any advice? Thanks in advance Mike -- Michael Pearmain Senior Analytics Research Specialist Statistics are like women; mirrors of purest virtue and truth, or like whores to use as one pleases Google UK Ltd Belgrave House 76 Buckingham Palace Road London SW1W 9TQ United Kingdom t +44 (0) 2032191684 mpearm...@google.com If you received this communication by mistake, please don't forward it to anyone else (it may contain confidential or privileged information), please erase all copies of it, including all attachments, and please let the sender know it went to the wrong person. Thanks. [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Help with nls and error messages singular gradient
Hi, Michael,
I think the SPSS answer is wrong. Your starting values are way off.
Look at this plot for verification:
con <- textConnection("time bod
11 0.47
22 0.74
33 1.17
44 1.42
55 1.60
67 1.84
79 2.19
8 11 2.17")
mydata <- read.table(con, header = TRUE)
close(con)
beta <- c(3, -0.1) # your initial values
beta <- c(2.4979, -2.02456) # SPSS answer
mycurve <- function(x) {
beta[1]/(1 - exp(beta[1] * x))
}
curve(mycurve, from = 1, to = 11,
ylim = range(mydata$bod, mycurve(mydata$time)))
points(mydata$time, mydata$bod)
You might want to look at package nls2 which allows a brute force grid
search to find some starting values. Or rethink the equation you're
trying to fit.
HTH,
--sundar
On Tue, Aug 25, 2009 at 9:10 AM, Michael Pearmain wrote:
> Hi All,
>
> I'm trying to run nls on the data from the study by Marske (Biochemical
> Oxygen Demand Interpretation Using Sum of Squares Surface. M.S. thesis,
> University of Wisconsin, Madison, 1967) and was reported in Bates and Watts
> (1988).
>
> Data is as follows, (stored as mydata)
>
> time bod
> 1 1 0.47
> 2 2 0.74
> 3 3 1.17
> 4 4 1.42
> 5 5 1.60
> 6 7 1.84
> 7 9 2.19
> 8 11 2.17
>
> I then run the following;
> #Plot initial curve
> plot(mydata$time, mydata$bod,xlab="Time (in days)",ylab="biochemical oxygen
> demand (mg/l) ")
>
> model <- nls(bod ~ beta1/(1 - exp(beta2*time)), data =
> mydata, start=list(beta1 = 3, beta2 = -0.1),trace=T)
>
> The start values are recommended, (I have used these values in SPSS without
> any problems, SPSS returns values of Beta1 = 2.4979 and Beta2 = -2.02 456)
>
> but return the error message,
> Error in nls(bod ~ beta1/(1 - exp(beta2 * time)), data = mydata, start =
> list(beta1 = 3, : singular gradient
>
> Can anyone offer any advice?
>
> Thanks in advance
>
> Mike
>
>
>
>
>
>
>
>
>
> --
> Michael Pearmain
> Senior Analytics Research Specialist
>
> “Statistics are like women; mirrors of purest virtue and truth, or like
> whores to use as one pleases”
>
> Google UK Ltd
> Belgrave House
> 76 Buckingham Palace Road
> London SW1W 9TQ
> United Kingdom
> t +44 (0) 2032191684
> mpearm...@google.com
>
> If you received this communication by mistake, please don't forward it to
> anyone else (it may contain confidential or privileged information), please
> erase all copies of it, including all attachments, and please let the sender
> know it went to the wrong person. Thanks.
>
> [[alternative HTML version deleted]]
>
>
> __
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
>
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] Help with nls and error messages singular gradient
Another alternative is to use SSlogis which is very similar to the
model you're fitting except with one additional parameter:
Asym <- 3
xmid <- 0
scal <- 10
model <- nls(bod ~ SSlogis(time, Asym, xmid, scal), data = mydata)
summary(model)
plot(bod ~ time, mydata)
newdata <- data.frame(time = seq(1, 11, length = 100))
lines(newdata$time, predict(model, newdata))
HTH,
--sundar
On Tue, Aug 25, 2009 at 10:05 AM, Sundar Dorai-Raj wrote:
> Hi, Michael,
>
> I think the SPSS answer is wrong. Your starting values are way off.
> Look at this plot for verification:
>
> con <- textConnection("time bod
> 1 1 0.47
> 2 2 0.74
> 3 3 1.17
> 4 4 1.42
> 5 5 1.60
> 6 7 1.84
> 7 9 2.19
> 8 11 2.17")
> mydata <- read.table(con, header = TRUE)
> close(con)
>
> beta <- c(3, -0.1) # your initial values
> beta <- c(2.4979, -2.02456) # SPSS answer
> mycurve <- function(x) {
> beta[1]/(1 - exp(beta[1] * x))
> }
> curve(mycurve, from = 1, to = 11,
> ylim = range(mydata$bod, mycurve(mydata$time)))
> points(mydata$time, mydata$bod)
>
> You might want to look at package nls2 which allows a brute force grid
> search to find some starting values. Or rethink the equation you're
> trying to fit.
>
> HTH,
>
> --sundar
>
> On Tue, Aug 25, 2009 at 9:10 AM, Michael Pearmain wrote:
>> Hi All,
>>
>> I'm trying to run nls on the data from the study by Marske (Biochemical
>> Oxygen Demand Interpretation Using Sum of Squares Surface. M.S. thesis,
>> University of Wisconsin, Madison, 1967) and was reported in Bates and Watts
>> (1988).
>>
>> Data is as follows, (stored as mydata)
>>
>> time bod
>> 1 1 0.47
>> 2 2 0.74
>> 3 3 1.17
>> 4 4 1.42
>> 5 5 1.60
>> 6 7 1.84
>> 7 9 2.19
>> 8 11 2.17
>>
>> I then run the following;
>> #Plot initial curve
>> plot(mydata$time, mydata$bod,xlab="Time (in days)",ylab="biochemical oxygen
>> demand (mg/l) ")
>>
>> model <- nls(bod ~ beta1/(1 - exp(beta2*time)), data =
>> mydata, start=list(beta1 = 3, beta2 = -0.1),trace=T)
>>
>> The start values are recommended, (I have used these values in SPSS without
>> any problems, SPSS returns values of Beta1 = 2.4979 and Beta2 = -2.02 456)
>>
>> but return the error message,
>> Error in nls(bod ~ beta1/(1 - exp(beta2 * time)), data = mydata, start =
>> list(beta1 = 3, : singular gradient
>>
>> Can anyone offer any advice?
>>
>> Thanks in advance
>>
>> Mike
>>
>>
>>
>>
>>
>>
>>
>>
>>
>> --
>> Michael Pearmain
>> Senior Analytics Research Specialist
>>
>> “Statistics are like women; mirrors of purest virtue and truth, or like
>> whores to use as one pleases”
>>
>> Google UK Ltd
>> Belgrave House
>> 76 Buckingham Palace Road
>> London SW1W 9TQ
>> United Kingdom
>> t +44 (0) 2032191684
>> mpearm...@google.com
>>
>> If you received this communication by mistake, please don't forward it to
>> anyone else (it may contain confidential or privileged information), please
>> erase all copies of it, including all attachments, and please let the sender
>> know it went to the wrong person. Thanks.
>>
>> [[alternative HTML version deleted]]
>>
>>
>> __
>> R-help@r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>>
>
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
