On Wed, Apr 27, 2011 at 12:44 PM, Patrick Burns
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 <- data.frame(
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
xpsPreproce
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 t
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 fo
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 probabl
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
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
On Tue, Apr 26, 2011 at 7:39 PM, Duncan Murdoch
wrote:
> If you don't like the way this was done in my three lines above, or by Frank
> Harrell, or the Zelig group, or John Fox, why don't you do it yourself, and
> get it right this time? It's pretty rude to complain about things that
> others ha
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 t
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 ra
On Wed, Apr 27, 2011 at 3:55 AM, peter dalgaard 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 tim
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
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
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