[R-SIG-Mac] predict.lm error

[Prof Brian Ripley]

Please, R 2.5.1 is long obsolete.  As the R posting guide says, update 
your R *before* posting.  At this point (with pre-releases of R 2.7.2 
imminent), please try a daily build of R-patched.

It seems a problem with the quartz() device, and that has been completely 
rewitten since.

Your code is not directly reproducible: it is unhelpful not to give an 
example which can just be pasted in.

On Tue, 12 Aug 2008, Robert Chatfield wrote:

> qqplot(z,z.predict$fit)
> 2008-08-12 16:59:58.105 R[3203] *** Assertion failure in -
> [RDeviceView lockFocus], AppKit.subproj/NSView.m:3248
> 2008-08-12 16:59:58.105 R[3203] *** REngine.runREPL: caught ObjC
> exception in the main loop!
> *** Please report the following error on r-sig-mac at r-project.org
> along with the full description of how to reproduce it:
> *** reason: lockFocus sent to a view whose window is deferred and
> does not yet have a corresponding platform window
> *** name: NSInternalInconsistencyException, info: (null)
> *** Version: R 2.5.1 (42083) R.app R 2.5.1 GUI 1.20 (4535)/i386
> Consider saving your work soon in case this problem leads to a full
> crash.
>
>
> context:  Trying to understand the meaning of predict in the case of
> predict.lm
>
> error occurs with qqplot(z,z.predict$fit)  of very much different
> length vectors (z a matrix)
>
> predict.lm is supplied 40000 x,y pairs  for a two-parameter regression,
> but
>
> length(z.predict$fit) is only 4912
>
> Code follows here
>
> #
> x.jH.min = 10^x.ljH.min
> x.jH.max=  10^x.ljH.max
> y.NO.min=10^y.lNO.min
> y.NO.max=10^y.lNO.max
> #
> x.jH.set = seq(x.jH.min, x.jH.max, by=x.jH.max/200)
> y.NO.set = seq(y.NO.min, y.NO.max, by=y.NO.max/200)
> #
> n.x.jH.set = length(x.jH.set)
> n.y.NO.set = length(y.NO.set)
> x.d = vector(mode="numeric",length=n.x.jH.set*n.y.NO.set)
> y.d = vector(mode="numeric",length=n.x.jH.set*n.y.NO.set)
> length(x.d)
> #
> z = matrix(nrow=length(x.jH.set),ncol=length(y.NO.set))
> dim(z)
> z=matrix(nrow=n.x.jH.set,ncol=n.y.NO.set)
> dim(z)
> ind.d = 1
> for ( xi  in seq(1,n.x.jH.set) ) {
> 	xx = x.jH.set[xi]
> 	for ( yi in seq(1,n.y.NO.set) ) {
> 		yy = y.NO.set[yi]
> 		z[xi,yj] = 10^(coefficients(logfit.wt.lm)[1] + coefficients
> (logfit.wt.lm)[2]*log10(xx) + coefficients(logfit.wt.lm)[3]*log10(yy))
> 		x.d[ind.d] = xx
> 		y.d[ind.d] = yy
> 		ind.d = ind.d + 1
> 		}
> 	}
> ########################################################################
> ############
> #
> xy.d = data.frame(cbind(x.d,y.d))
> names(xy.d)=c("x","y")
>
> z.predict=predict(logfit.wt.lm,data=xy.d,se.fit = TRUE)
>
>
>
> ASSUMPTIONS
> ...where these condistions are more or less all you need to run the
> code snippet.
> > length(x.d)
> [1] 40000
> > x.ljH.min
> [1] 7.75
> > x.ljH.max
> [1] 10.25
> > y.lNO.min
> [1] 9.75
> > y.lNO.max
> [1] 12.25
> >
>
> > coefficients(logfit.wt.lm
> + )
> (Intercept)  l.j.HCHO.m      l.NO.m
>  -0.4214285   0.4190370   0.5483868
> >
> 	[[alternative HTML version deleted]]
>
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>

-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595