That is not an appropriate way to fit a degree-10 polynomial (in any
language, if fitting a degree-10 polynomial is in fact an appropriate
statistical analysis, which seems unlikely).
On Sun, 30 Jul 2006, Carnell, Rob C wrote:
> NIST maintains a repository of Statistical Reference Datasets at
>
NIST maintains a repository of Statistical Reference Datasets at
http://www.itl.nist.gov/div898/strd/. I have been working through the
datasets to compare R's results to their references with the hope that
if all works well, this could become a validation package.
All the linear regression datase
Thanks, that works splendidly.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email [EMAIL PROTECTED] Department of Economics
vox:217-333-4558University of Illinois
fax:217-244-6678Champaign, IL
There is no reason to add ...: you could have
binomial(link = Gosset(nu=5)).
I really don't like the idea of changing system functions like make.link,
and believe it is not necessary.
On Sun, 30 Jul 2006, roger koenker wrote:
> At useR 2006 I mentioned that it would be nice to have a way to
At useR 2006 I mentioned that it would be nice to have a way to
specify binomial links
that involved free parameters and described some experience with a
Gosset link involving
a free degrees of freedom parameter, and a Tukey-lambda link with two
free parameters.
My implementation of this inv
Robert Gentleman <[EMAIL PROTECTED]> writes:
> OK, that suggests setting at the options level would solve both of your
> problems and that seems like the best approach. I don't really want to
> pass this around as a parameter through the maze of functions that might
> actually download something
Hi Bill,
After playing with this some more and adding an implementation to
handle NAs in the data vector, I have run into the problem of what to
return when the only data values for a particular bin (or level) in
the data vector were NAs and the user selected na.rm=T
1. Should it return 0 f
Kevin, starting with your idea of sorting first, you can get some speedups
just using R. Start by comparing the base case that Bill used:
> x <- runif(2e6)
> i <- rep(1:1e6, 2)
> unix.time(res0 <- unlist(lapply(split(x,i), sum)))
[1] 11.00 0.16 11.28NANA
Now, try sorting and using a lo
