Hi all,
I am working on a bug, which running PLR on HAWQ. The process hung and
can't be terminated.
>From my investigation, it seems signal handler 'Rf_onsigusr1' trigger a
malloc/free deadlock.
The calling stack is below.
Thread 1 (Thread 0x7f4c93af48e0 (LWP 431263)):
#0 0x7f4c9015805e i
Dear Samsad,
The usual use of the arcsine transformation for proportions is
arcsine-squareroot. Thus, in R, for proportions in p, you can use
asin(sqrt(p)).
You could have found the asin() function yourself in several ways, including
help.search("arcsin"), which turns up the help page for tri
Thierry: thanks much for your feedback, and apologies for this tardy response.
You pointed me in the right direction. I did not appreciate how even if the
algorithm ultimately has O(n^2) behavior, it can take a big n to overcome large
coefficents on lower order terms (e.g. the O(1) and O(n) par
> On Jul 31, 2016, at 8:07 AM, Bhaskar Mitra wrote:
>
> Hello Everyone,
>
>
> I have a data frame with 2 columns as shown at the end of this mail. I want
> to plot the data in column A;
> however I want the data-points in column A to be of different color based
> on conditions in column B.
>
On Sun, 31 Jul 2016, Samsad Afrin Himi wrote:
Dear R-Team,
How can I do arcsine tzransformation in R? My data is proportional score.
?asin
Could you please help me out?
This is such a simple task that it is difficult to tell what very basic
aspects of R you need help with. If you don't
Hello Everyone,
I have a data frame with 2 columns as shown at the end of this mail. I want
to plot the data in column A;
however I want the data-points in column A to be of different color based
on conditions in column B.
i.e all data in column A corresponding to value 0 in column B should be
Dear R-Team,
How can I do arcsine tzransformation in R? My data is proportional score.
Could you please help me out?
Best,
Samsad
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> On Jul 30, 2016, at 7:53 PM, roslinazairimah zakaria
> wrote:
>
> Dear r-users,
>
> I would like to use lapply for the following task:
>
> ## Kolmogorov-Smirnov
> ks.test(stn_all[,1][stn_all[,1] > 0],stn_all_gen[,1][stn_all_gen[,1] > 0])
> ks.test(stn_all[,2][stn_all[,2] > 0],stn_all_gen[,2
Hi Marco
Thanks for your prompt reply.
First, I have been using the parse(eval()) convention because I saw it
used in some example code for running cpquery, but am happy to drop this
practice.
I have tried running the cpquery in the debug mode, and found that it
typically returns the following f
Hi Jeff,
many thanks, that one is the Speedy Gonzalles out of all. Can also do some FUN
stuff.
aggregate.nx.ny.array.aperm <- function( dta, nx = 2, ny = 2, FUN=colMeans, ...
) {
# number of rows in result
nnr <- nrow( dta ) %/% ny
# number of columns in result
nnc <- ncol( dta ) %/% nx
#
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