On Apr 27, 2011, at 02:39 , Duncan Murdoch wrote:
On 26/04/2011 11:13 AM, Paul Johnson wrote:
Is anybody working on a way to standardize the creation of newdata
objects for predict methods?
[snip]
I think it is time the R Core Team would look at this tell us what
is the right way to do
On 26.04.2011 21:58, cstrato wrote:
Dear Duncan, dear Uwe,
Just now I have re-run everything, and today xps.Rnw can be converted to
a vignette w/o any problems using:
a, buildVignettes(xps, dir=/Volumes/CoreData/CRAN/xps, quiet=F)
b, R CMD Sweave xps.Rnw
In both cases the vignette xps.pdf is
On Wed, Apr 27, 2011 at 3:55 AM, peter dalgaard pda...@gmail.com wrote:
On Apr 27, 2011, at 02:39 , Duncan Murdoch wrote:
On 26/04/2011 11:13 AM, Paul Johnson wrote:
Is anybody working on a way to standardize the creation of newdata
objects for predict methods?
[snip]
I think it is time
On Wed, 2011-04-27 at 12:00 +0200, Peter Dalgaard wrote:
Er... No, I don't think Paul is being particularly rude here (and he
has been doing us some substantial favors in the past, notably his
useful Rtips page). I know the kind of functionality he is looking
for; e.g., SAS JMP has some
Hi useRs,
As the maintainer of the Distribution task view (
http://cran.r-project.org/web/views/Distributions.html) for more than two
years, the following feedback exercise should have been done earlier. But
late is better than never!
I start this discussion to get your feedbacks/suggestions on
Among many solutions, I generally use the following code, which avoids the
ideal average individual, by considering the mean across of the predicted
values:
averagingpredict - function(model, varname, varseq, type, subset=NULL)
{
if(is.null(subset))
mydata - model$data
else
Here are some data frames:
df3.2 - data.frame(1:3, 7:9)
df4.2 - data.frame(1:4, 7:10)
df3.3 - data.frame(1:3, 7:9, 10:12)
df4.3 - data.frame(1:4, 7:10, 10:13)
df3.4 - data.frame(1:3, 7:9, 10:12, 15:17)
df4.4 - data.frame(1:4, 7:10, 10:13, 15:18)
Now here are some commands and their answers:
On Apr 27, 2011, at 19:44 , Patrick Burns wrote:
I would think a method in analogy to
'mean.data.frame' would be a logical choice.
But I'm presuming there might be an argument
against that or 'median.data.frame' would already
exist.
Only if someone had a better plan. As you are probably
Hi Simon,
That makes a lot of sense to me. I'll start reading about R's event loop
signaling. I'm not sure what the best method will be for me to flag the
completeness of a threaded process in my case. In abstract it seems that I
could get R's event loop to look for any type of flag. I think key
Sean,
On Apr 27, 2011, at 3:21 PM, Sean Robert McGuffee wrote:
Hi Simon,
That makes a lot of sense to me. I'll start reading about R's event loop
signaling. I'm not sure what the best method will be for me to flag the
completeness of a threaded process in my case. In abstract it seems that
Dear Uwe,
As I have already mentioned R CMD check gives the following output:
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes in 'inst/doc' ... WARNING
Package vignette(s) without corresponding PDF:
APTvsXPS.Rnw
xps.Rnw
xpsClasses.Rnw
On Wed, Apr 27, 2011 at 12:44 PM, Patrick Burns
pbu...@pburns.seanet.com wrote:
Here are some data frames:
df3.2 - data.frame(1:3, 7:9)
df4.2 - data.frame(1:4, 7:10)
df3.3 - data.frame(1:3, 7:9, 10:12)
df4.3 - data.frame(1:4, 7:10, 10:13)
df3.4 - data.frame(1:3, 7:9, 10:12, 15:17)
df4.4 -
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