On Jul 18, 2011, at 10:13 AM, Steven Ranney wrote:
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,
No. You did not give us a dataset in the sense that the word
"reproducible" implies when used in the tag-line of r-help. You gave
us a console print representation. Considerable ambiguity remains. Had
you posted dput(data_object) , or if you had responded constructively
to Ehler's suggesting to post str() output, we might not have wasted
all this time guessing.
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),
After noting your error below .... I don't think the naming of terms
in the internal processing will carry along the "as.numeric" function
to the final names of the terms. And furthermore why would input to
nls not already _be_ numeric? You aren't dealing with a factor object
are you? In that case you are not making the conversion correctly and
you need to read the FAQ on the topic of factor conversion.
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)))
Sometimes I worry that I am starting to view the printed word exactly
as my R parser would. That looks ... just wrong. How do you expect
this to be parsed:
list(as.numeric(x) = modb)
The name of the list item in the result would be ... what?
`as.numeric(x)`? That could be a real mess. Fortunately, an error is
thrown.
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 you don't offer the code?
but I end up with
Error in xy.coords(x, y) : 'x' and 'y' lengths differ
So we have not way of commenting on that error, now, do we?
-- David.
SR
Steven H. Ranney
On Mon, Jul 18, 2011 at 7:52 AM, Peter Ehlers <ehl...@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<ehl...@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@r-project.org mailing list
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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.
David Winsemius, MD
West Hartford, CT
______________________________________________
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.
