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@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
 > 
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