From: Richard Chandler <rchandler_at_forwild.umass.edu>

Date: Sun 22 Jan 2006 - 09:28:27 EST

Date: Sun 22 Jan 2006 - 09:28:27 EST

Please ignore my last message, I've realized that Peter's first reply was all I needed...thanks.

Richard

Quoting Richard Chandler <rchandler@forwild.umass.edu>:

> Sorry that was a typo when I said 'resposnse'... I meant predictor.

*> I
**> want to fit lm(y ~ log(x)) and plot the line with confidence
**> intervals on a log="x" plot so that I can see the real units of x
**> rather than the log(x) units. I can't get the real line using
**> predict.lm() without removing the log() from the formula. Thanks
**> again.
**>
**> Quoting Peter Dalgaard <p.dalgaard@biostat.ku.dk>:
**>
**> > Richard Chandler <rchandler@forwild.umass.edu> writes:
**> >
**> > > Thanks for the reply though I don't think your suggestion
**> worked.
**> > I
**> > > have found a way to get the correct line though it is not
**> > > convenient.
**> > >
**> > > x <- 1:100
**> > > y <- 1:100
**> > > plot(y ~ x, log="x")
**> > >
**> > > #The only way I can get the correct line is to drop the log():
**> > > abline(lm(y ~ x), untf=T, lwd=2) #or
**> > > lines(x, predict(lm(y ~ x)), col=2)
**> > >
**> > > #Neither of these work
**> > > abline(lm(y ~ log10(x))) #or
**> > > abline(lm(y ~ log10(x)), untf=T)
**> > >
**> > > What I really would like to do is plot fitted lines and 95%
**> > > confidence intervals using predict.lm, as in shown in the
**> > example,
**> > > but when the predictor is log transformed and log="x". I can't
**> > figure
**> > > out how to do this without removing the log() from the
**> response
**> > part
**> > > of the formula and this isn't helpful because I'm generally
**> > trying to
**> > > give predict() a fitted object rather than a lm() formula. I
**> > still
**> > > think I'm probably missing something simple but are there any
**> > other
**> > > suggestions? Thanks.
**> > >
**> >
**> > First decide what you really want. I see log() hopping all over
**> > the
**> > place. Is it on the response or the predictor? Do you want a
**> > straight
**> > line on an x-logged plot or an x-logged plot of a straight line?
**> > Do
**> > you intend to fit y~x or y~log(x) ?
**> >
**> >
**> >
**> > > Richard
**> > >
**> > >
**> > > Quoting Peter Dalgaard <p.dalgaard@biostat.ku.dk>:
**> > >
**> > > > Richard Chandler <rchandler@forwild.umass.edu> writes:
**> > > >
**> > > > > Hello,
**> > > > >
**> > > > > I'm trying to plot a fitted lm() line on a plot when the
**> one
**> > > > > explanatory variable is log transformed and log="x". I get
**> > > > different
**> > > > > lines using abline and predict.lm().
**> > > > >
**> > > > > #Example
**> > > > > x <- 1:100
**> > > > > y <- rnorm(100)
**> > > > > plot(y ~ x, log="x")
**> > > > > abline(lm(y ~ log(x)))
**> > > > > lines(x, predict(lm(y ~ log(x))), lwd=2)
**> > > > >
**> > > > > I'm sure I'm missing something but could someone tell me
**> > which
**> > > > line is
**> > > > > correct? Thanks.
**> > > >
**> > > > Base 10 is what you're missing.
**> > > >
**> > > > The latter form is agnostic with respect to base, the former
**> > is
**> > > > not
**> > > > (since the fitted values are the same, but regression
**> > coefficients
**> > > > differ). So you need to know to use abline(lm(y ~
**> log10(x))).
**> > > >
**> > > > You don't really notice which kind of log is being used
**> until
**> > you
**> > > > look
**> > > > at par(usr) for a plot with logged axes.
**> > > >
**> > > > --
**> > > > O__ ---- Peter Dalgaard ุster Farimagsgade
**> 5,
**> > > > Entr.B
**> > > > c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014
**> Cph.
**> > K
**> > > > (*) \(*) -- University of Copenhagen Denmark Ph:
**>
**> > (+45)
**> > > > 35327918
**> > > > ~~~~~~~~~~ - (p.dalgaard@biostat.ku.dk)
**> FAX:
**> > (+45)
**> > > > 35327907
**> > > >
**> > >
**> > >
**> > > --
**> > > Richard Chandler, M.S. candidate
**> > > Department of Natural Resources Conservation
**> > > UMass Amherst
**> > > (413)545-1237
**> > >
**> >
**> > --
**> > O__ ---- Peter Dalgaard ุster Farimagsgade 5,
**> > Entr.B
**> > c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K
**> > (*) \(*) -- University of Copenhagen Denmark Ph:
**> (+45)
**> > 35327918
**> > ~~~~~~~~~~ - (p.dalgaard@biostat.ku.dk) FAX:
**> (+45)
**> > 35327907
**> >
**>
**>
**> --
**> Richard Chandler, M.S. candidate
**> Department of Natural Resources Conservation
**> UMass Amherst
**> (413)545-1237
*

-- Richard Chandler, M.S. candidate Department of Natural Resources Conservation UMass Amherst (413)545-1237 ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.htmlReceived on Sun Jan 22 09:50:57 2006

*
This archive was generated by hypermail 2.1.8
: Sun 22 Jan 2006 - 14:10:30 EST
*