similar to: split() is slow on data.frame (PR#14123)

hi, I met some problems in R, plz help me. 1. How to do a intersect operation among several groups in one list, without a loop statement? (I think It may be a list) create data: myData <- data.frame(product = c(1,2,3,1,2,3,1,2,2), year=c(2009,2009,2009,2010,2010,2010,2011,2011,2011),value=c(1104,608,606,1504,508,1312,900,1100,800)) mySplit<- split(myData,myData$year)

How does one implement a likelihood-ratio test, to test whether the variances of the random effects differ between two groups of subjects? Suppose your data consist of repeated measures on subjects belonging to two groups, say boys and girls, and you are fitting a linear mixed-effects model for the response as a function of time. The within-subject errors (residuals) have the same variance in

Hello, I'll use part of the iris dataset for an example of what I want to do. > data(iris) > iris<-iris[1:10,1:4] > iris Sepal.Length Sepal.Width Petal.Length Petal.Width 1 5.1 3.5 1.4 0.2 2 4.9 3.0 1.4 0.2 3 4.7 3.2 1.3 0.2 4 4.6 3.1 1.5

There are a number of functions that are dispatched to from split(). > methods('split') [1] split.data.frame split.Date split.default split.POSIXct Is there a way to figure out which of these variants is actually dispatched to when I call split? I know that if the argument is of the type data.frame, split.data.frame will be called? Is it the case that if the argument is not

On Thu, 4 Feb 2010, Conrad Parker wrote: >> Would there be any interest in hosting this alongside the current >> (definately write-only) java library? > > of course, the more better implementations the better! what vcs are you > using? Currently the vcs isn't anywhere public. I've dropped a snapshot at http://gagravarr.org/misc/vj-20100204-1.tar.gz in case

M P?opklpnlbyj?nvnmm M. ?plppkbkv??k? knbnnnnnn??????llp?????tx hikkkhgxxx vj jul?l Sent from my iPhonejukuj?b?mjl jnmnmmm Sorry for keeping things short Gustaf Granath (phd) Plant Ecology Uppsala University

I don't see where describes the implementation of '[]'. For example, if x is a matrix or a data.frame, how the lookup of 'colname1' is x[, 'colname1'] executed. Does R perform a lookup in the a hash of the colnames? Is the reference O(1) or O(n), where n is the second dim of x?

I don't see where describes the implementation of '[]'. For example, if x is a matrix or a data.frame, how the lookup of 'colname1' is x[, 'colname1'] executed. Does R perform a lookup in the a hash of the colnames? Is the reference O(1) or O(n), where n is the second dim of x?

On Wed, Jan 28, 2015 at 7:50 AM, Hal Finkel <hfinkel at anl.gov> wrote: > Hi Vijender, > > Thanks for posting this, there is wide support here for improving our support for reductions of various kinds, both in flavor and robustness. I've cc'd some others who have previously discussed this. > > James has advocated in the past for an intrinsic for horizontal reductions,

Dear users, I am attempting to plot an ols() call from the Design package, by following the procedure explained by Harald Baayen in his 2008 book 'Analyzing linguistic data. A practical introduction to statistics using R', page 175-181. I've attached my data to this e-mail (I hope it's small enough that that's ok). First I paste all the commands I ran, followed by the

Hi, I am interested in generating two different optimized versions of a function into a single binary, so that I can dynamically select the function to execute at runtime. Can anyone shed some insight into the difficulties in achieving this in the LLVM infrastructure? Thank you! vj. -------------- next part -------------- An HTML attachment was scrubbed... URL:

Hi Community. I have at least just one short question. Is it possible to configure SAMBA in a way, that it notice the password change on Winn 2000 or Win XP system and adjust this password change in it's one password file without using LDAP or other password server? Thanks VJ

I have the following code, which tests the split on a data.frame and the split on each column (as vector) separately. The runtimes are of 10 time difference. When m and k increase, the difference become even bigger. I'm wondering why the performance on data.frame is so bad. Is it a bug in R? Can it be improved? > system.time(split(as.data.frame(x),f)) user system elapsed 1.700

Hi, > x=c(rep(1,3),rep(3,2)) > x [1] 1 1 1 3 3 > duplicated(x) [1] FALSE TRUE TRUE FALSE TRUE > As shown in the above code, 'duplicated' doesn't return 'F' for the first '1' and first '3' in 'x'. I am wondering if there is a function that can return an indicator for any element whether it appears in a vector twice or more. Regards, Peng

I can exclude columns by column number using '-'. But I wondering if there is an easy way to exclude some columns by column names. > x=cbind(c(1,2),c(3,4)) > x [,1] [,2] [1,] 1 3 [2,] 2 4 > colnames(x)=c('a','b') > x a b [1,] 1 3 [2,] 2 4 > x[,-'a'] Error in -"a" : invalid argument to unary operator > x[,-1] [1] 3 4

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Release Announcements ===================== This is a security release in order to address CVE-2009-0022. o CVE-2009-0022 In Samba 3.2.0 to 3.2.6, in setups with registry shares enabled, access to the root filesystem ("/") is granted when connecting to a share called "" (empty string) using old versions of

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Release Announcements ===================== This is a security release in order to address CVE-2009-0022. o CVE-2009-0022 In Samba 3.2.0 to 3.2.6, in setups with registry shares enabled, access to the root filesystem ("/") is granted when connecting to a share called "" (empty string) using old versions of

Hi, There are quiet a few different 'apply' functions, such as lapply, sapply and many more. I'm very familiar with the 'Apply' function in Mathematica. Can somebody point me a summary of all the 'apply' functions in R. Also, I'm curious that what 'l' and 's' (and other prefixes) stand for in 'lapply' and 'sapply' Regards, Peng

Here is a problem that perhaps someone out here has an idea about. It vaguely reminds me of something I've seen before, but can't place. Can anyone help? For multiple imputation, there are simpler methods available if the patterns of missing data are 'monotone' --- if Vj is missing then all variables Vk, k>j are also missing, vs. more complex methods required when the

HI, When we run wine <program.exe>, it looks like wine by default tries to pick up files from drive_c\windows\system32. What do we do if the executable files are installed in a different location?. Wine cannot load it and fails. Is there a PATH variable or something we can set for WINE, just like we set in a OS? Cheers