plotting predicted values (lines) over data?

Dear Jeff,

I'm not sure that I follow entirely what you've done, but perhaps the 
following suggestions will help: (1) If the plotted curve isn't smooth 
because it's evaluated at too few x-values or at x-values that are too 
unevenly spaced, what about getting a sufficient number of predicted values 
[via predict()] that are evenly spaced along the range of ht -- i.e., not 
at the observations? (2) Rather than connecting the fitted values with line 
segments, you could use spline() to interpolate.

I hope that this helps,
  John

I've been trying to plot the predicted values, as a line, over the data for
a simple nonlinear fit with the following commands:

plot( hg ~ ht )
... define some function hg ~ ht + junk ...
... blah, blah, obtain parameter estimates and predicted values, blah...
... then...
lines( sort( $predicted ) ~ sort( ht ) )

which results in a line that isn't smooth (which I knew would happen). I've
checked the FAQ,docs and archives and I'm not sure if there's function that
will so what Heut et. al (2004) do with their plfit(). So, is there already
an R function, or process to do this, or will I have to write one?

Thanks,
Jeff.

-----------------------------------------------------
John Fox
Department of Sociology
McMaster University
Hamilton, Ontario, Canada L8S 4M4
email: jfox at mcmaster.ca
phone: 905-525-9140x23604
web: www.socsci.mcmaster.ca/jfox