[R] nls() and lines()
Steven Ranney
steven.ranney at gmail.com
Mon Jul 18 16:13:51 CEST 2011
Unfortunately, the transposition of lines and list was a typo on my
part. Now that I look like a fool and have corrected the issue, I'm
still faced with the same dilemma. With the original data set I
posted in this thread,
plot(mpg~x, data=mileage[year==2009,], ylab="Miles per gallon",
xlab="2009", yaxs="i", ylim=c(10,30))
nls.2009 <- nls(mpg~(alpha*(as.numeric(x)^2))+(bravo*as.numeric(x))+(charlie),
data=mileage[year==2009,], start=list(alpha=-2e-14, bravo=5e-5,
charlie=-31407),
trace=T, na.action=na.omit, nls.control(minFactor=0.000000000000000000001))
plot(mpg~x, data=mileage[year==2009,])
modb=seq(min(as.numeric(x)), max(as.numeric(x)), by=10000)#; modb
lines(modb, predict(nls.2009, list(as.numeric(x) = modb)))
The last line returns the following error:
Error: unexpected '=' in " lines(modb, predict(nls.2009, list(as.numeric(x) ="
I've tried putting in modb as the "newdata" in the predict()
statement, but I end up with
Error in xy.coords(x, y) : 'x' and 'y' lengths differ
SR
Steven H. Ranney
On Mon, Jul 18, 2011 at 7:52 AM, Peter Ehlers <ehlers at ucalgary.ca> wrote:
> On 2011-07-18 06:38, Steven Ranney wrote:
>>
>> Provided, of course, that I alter the lines for different data sets
>> and data frames, the code to plot a line derived from nls() onto a
>> plot works with no problems.
>>
>> Here's an example:
>>
>> Year NOP
>> 2002 6
>> 2003 8
>> 2004 11
>> 2005 19
>> 2006 26
>> 2007 25
>>
>> mod1<- nls(NOP~alpha*exp(beta*Year), data=aic,
>> start=list(alpha=1e-278, beta=0.3205), trace=T,
>> nls.control(maxiter=30000, minFactor=0.000005))
>> plot(NOP~Year, data=aic, pch=19, ylab="Number of papers")
>> mod1a=seq(2002, 2007, by=.0001)
>> lines(mod1a, predict(mod1, list(Year = mod1a)))
>
> Yes, but here's what you posted as your 'last line of code':
>
> lines(modb, predict(nls.2009, lines(as.numeric(x)=modb)))
>
> Perhaps just a typo: lines -> list???
> In any case, the newdata in predict should have a variable 'Year'.
>
> Peter Ehlers
>
>>
>> I've been using this code for several years not to get models from
>> nls() onto plot and I've never had an issue with it until the dataset
>> I referenced in my initial email.
>>
>> Thanks for your assistance.
>>
>> SR
>>
>> Steven H. Ranney
>>
>> http://www.steven-ranney.com
>> http://stevenranney.blogspot.com
>>
>>
>> On Mon, Jul 18, 2011 at 2:55 AM, Peter Ehlers<ehlers at ucalgary.ca> wrote:
>>>
>>> On 2011-07-17 17:37, Steven Ranney wrote:
>>>>
>>>> All -
>>>>
>>>> I'm having an issue with trying to plot a model derived from nls()
>>>> onto a simple plot. I have included a sample data set and the code
>>>> that I've been using.
>>>>
>>>> year month day date location mileage cost gallon cpg
>>>> mpg x
>>>> 2009 1 4 1/4/2009 BZN 124585 19.39 14.37 1.349339
>>>> 10.71677 2009-01-04
>>>> 2009 1 15 1/15/2009 BZN 124888 23.2 16.12 1.439206
>>>> 18.79653 2009-01-15
>>>> 2009 1 27 1/27/2009 BZN 125133 21.51 14.35 1.498955
>>>> 17.07317 2009-01-27
>>>> 2009 2 16 2/16/2009 BZN 125429 27.96 15.54 1.799228
>>>> 19.04762 2009-02-16
>>>> 2009 2 27 2/27/2009 BZN 125702 26.82 14.27 1.879467
>>>> 19.13104 2009-02-27
>>>> 2009 3 19 3/19/2009 BZN 125941 24.38 12.91 1.888459
>>>> 18.51278 2009-03-19
>>>> 2009 4 9 4/9/2009 BZN 126260 32.59 16.30 1.999387
>>>> 19.57055 2009-04-09
>>>> 2009 4 28 4/28/2009 BZN 126587 34.58 16.79 2.059559
>>>> 19.47588 2009-04-28
>>>> 2009 5 17 5/17/2009 BZN 126925 35.78 16.57 2.159324
>>>> 20.39831 2009-05-17
>>>> 2009 5 27 5/27/2009 BZN 127240 35.57 15.01 2.369753
>>>> 20.98601 2009-05-27
>>>> 2009 6 7 6/7/2009 BZN 127590 40.99 16.60 2.469277
>>>> 21.08434 2009-06-07
>>>> 2009 6 21 6/21/2009 BZN 127910 41.52 15.64 2.654731
>>>> 20.46036 2009-06-21
>>>> 2009 7 21 7/21/2009 BZN 128264 43.37 16.67 2.601680
>>>> 21.23575 2009-07-21
>>>> 2009 8 11 8/11/2009 BZN 128618 42.68 16.42 2.599269
>>>> 21.55907 2009-08-11
>>>> 2009 8 27 8/27/2009 BZN 128947 43.12 16.60 2.597590
>>>> 19.81928 2009-08-27
>>>> 2009 9 21 9/21/2009 BZN 129255 40.44 15.56 2.598972
>>>> 19.79434 2009-09-21
>>>> 2009 10 1 10/1/2009 BZN 129541 38.55 14.83 2.599461
>>>> 19.28523 2009-10-01
>>>> 2009 10 11 10/11/2009 BZN 129806 36.65 14.10 2.599291
>>>> 18.79433 2009-10-11
>>>> 2009 10 22 10/22/2009 BZN 130027 30.18 11.61 2.599483
>>>> 19.03531 2009-10-22
>>>> 2009 11 9 11/9/2009 BZN 130358 43.19 16.62 2.598676
>>>> 19.91576 2009-11-09
>>>> 2009 11 22 11/22/2009 BZN 130631 39.23 15.09 2.599735
>>>> 18.09145 2009-11-22
>>>> 2009 12 5 12/5/2009 BZN 130950 44.43 17.09 2.599766
>>>> 18.66589 2009-12-05
>>>> 2009 12 30 12/30/2009 BZN 131239 42.14 16.70 2.523353
>>>> 17.30539 2009-12-30
>>>>
>>>> After converting my dates into R-usable dates:
>>>>
>>>> #convert my dates to R-usable dates
>>>> x<- strptime(date, format="%m/%d/%Y")
>>>> x
>>>> mileage<- cbind(mileage, x)
>>>>
>>>> I plot the data and model mpg as a function of date. In the nls()
>>>> statement, I convert x back to a numeric value so that I can conduct
>>>> the regression:
>>>>
>>>> plot(mpg~x, data=mileage[year==2009,], ylab="Miles per gallon",
>>>> xlab="2009", yaxs="i", ylim=c(10,30))
>>>> nls.2009<-
>>>> nls(mpg~(alpha*(as.numeric(x)^2))+(bravo*as.numeric(x))+(charlie),
>>>> data=mileage[year==2009,], start=list(alpha=-2e-14, bravo=5e-5,
>>>> charlie=-31407),
>>>> trace=T, na.action=na.omit,
>>>> nls.control(minFactor=0.000000000000000000001))
>>>> plot(mpg~x, data=mileage[year==2009,])
>>>> modb=seq(min(as.numeric(x)), max(as.numeric(x)), by=10000)
>>>> lines(modb, predict(nls.2009, lines(as.numeric(x)=modb)))
>>>>
>>>> Unfortunately, when I run the final line of this code, I get the
>>>> following:
>>>>
>>>> Error: unexpected '=' in " lines(modb, predict(nls.2009,
>>>> lines(as.numeric(x)="
>>>>
>>>> In other similar analyses, I've been able to plot an nls() model using
>>>> this exact code--altered of course according to information--but here
>>>> I'm at a loss. I'm certain it has something to do with the
>>>> lines(...as.numeric(x)) value I'm trying to plot, but I can't figure
>>>> out what I'm doing wrong.
>>>
>>> That last line of code doesn't look right to me. The arguments
>>> that you need to supply to predict() are 'object' and 'newdata',
>>> where 'newdata' must have the appropriate form. Unless you have
>>> your own function lines(), I don't think that lines(as.numeric(x)=modb)
>>> would qualify as newdata.
>>>
>>> It's usually a bad idea to shove too much stuff into a single command
>>> and a good idea to use str() often.
>>>
>>> This 'exact' code worked in the past?
>>>
>>> Peter Ehlers
>>>
>>>>
>>>> The model is fine, but it's the plotting of the model that escapes me.
>>>>
>>>> I'm running R version 2.12.1 on a Windows 7 machine.
>>>>
>>>> Thanks for your help -
>>>>
>>>> Steven H. Ranney
>>>>
>>>> http://stevenranney.blogspost.com
>>>> http://www.steven-ranney.com
>>>>
>>>> ______________________________________________
>>>> R-help at 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.
>>>
>>>
>
>
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