similar to: problem with outer

I''m having this problem with IE and getElementsBySelector, but am a relative js novice, so quite possible -- likely even -- that I''m doing something stupid. Either way, a fresh pair of eyes would help. Basically I''m duplicating a fieldset within a form (so you can upload more than one photo). [BTW, the fieldsets have a CSS id which relates to the object id of the

On 07/29/2013 09:15 AM, Sven Verdoolaege wrote: > On Mon, Jul 29, 2013 at 07:37:14AM -0700, Tobias Grosser wrote: >> On 07/29/2013 03:18 AM, Sven Verdoolaege wrote: >>> On Sun, Jul 28, 2013 at 04:42:25PM -0700, Tobias Grosser wrote: >>>> Sven: In terms of making the behaviour of isl easier to understand, >>>> it may make sense to fail/assert in case

Hi Sebastian, Recently, I found the "Polly - Calculate dependences" pass would lead to significant compile-time overhead when compiling some loop-intensive source code. Tobias told me you found similar problem as follows: http://llvm.org/bugs/show_bug.cgi?id=14240 My evaluation shows that "Polly - Calculate dependences" pass consumes 96.4% of total compile-time overhead

Hello, I'm very new to using R, but I was told it could do what I want. I'm not sure how best to enter the information but here goes... I'm trying to transfer the following integral into R to solve for ln(gamma_1), on the left, for multiple instances of gamma_i and variable N_i. gamma_i is, for example, (0, 0.03012048, 0.05000000, 0.19200000, 0.44000000, 0.62566845) N_i (N_1 or

I'm wondering how odds ratio is computed. I thought that it is (n11/n12)/(n21/n22), but it is not what fisher.test() computes. Could somebody let me know? > n11=3 > n12=1 > n21=1 > n22=3 > > n1_=n11+n12 > n2_=n21+n22 > > n_1=n11+n21 > n_2=n12+n22 > > x=rbind(c(n11,n12),c(n21,n22)) > > threshold=dhyper(n11,n1_,n2_,n_1) >

Dear Tobias, Thank you very much for your very helpful advice. Yes, -debug-pass and -time-passes are two very useful and powerful options when evaluating the compile-time of each compiler pass. They are exactly what I need! With these options, I can step into details of the compile-time overhead of each pass. I have finished some preliminary testing based on two randomly selected files from

hey, my function doesn?t work. can somebody help me? the graphic doesn?t work and also the function. thnx a lot. N=10 n=100 p_0=c(1/5,1-1/5) power = function(p,m) { set.seed(1000) H=matrix(0,nrow=N,ncol=1) for(i in 1:N) { x <- matrix(rnorm(n, 0, 0.5), ncol = m) y <- matrix(rnorm(n, 0, 0.8), ncol = m) l <- diag(cor(x, y)) q_1 = qnorm(0.05, 0, 0.05) q_2 = qnorm(1 - 0.05, 0, 0.05)

On 04/30/2013 04:13 PM, Star Tan wrote: > Hi all, [...] > How could I find out where the time is spent on between two adjacent Polly passes? Can anyone give me some advice? Hi Star Tan, I propose to do the performance analysis using the 'opt' tool and optimizing LLVM-IR, instead of running it from within clang. For the 'opt' tool there are two commands that should help

On 05/03/2013 11:39 AM, Star Tan wrote: > Dear Tobias, > > > Thank you very much for your very helpful advice. > > > Yes, -debug-pass and -time-passes are two very useful and powerful > options when evaluating the compile-time of each compiler pass. They > are exactly what I need! With these options, I can step into details > of the compile-time overhead of each pass.

Hello! I have a csv file of intra-day financial data (5-min closing prices) that looks like this: (obs - the dates are formated as day/month/year, as is usual here in Brazil) Date;Time;Close 01/09/2009;10:00;56567 01/09/2009;10:05;56463 01/09/2009;10:10;56370 ##(goes on all day) 01/09/2009;16:45;55771 01/09/2009;16:50;55823 01/09/2009;16:55;55814 ##(jumps to the subsequent day)

I'm having trouble creating a looping variable and i can't see wher ethe problem arises from any hep gratfully appreciated First create a table x<-table(SURVEY$n_0,exposed) > x exposed False True Under 16 24 1 16-19 68 9 20-24 190 37 25-34 555 204 35-44 330 87 45-54 198 65 55-64 67 35 65+

Dear R users, how can I test, whether two correlations differ significantly. (I want to prove, that variables are correlated differently, depending on the group a person is in.) Greetings from Freiburg im Breisgau (Germany), Timo Stolz

Hi All, Newbie question that i'm sure is easy, but i can't seem to apply properly I read in a datafram from a CSV file and i want to tell R that from coloum "n_0" to "n_32" the value "-1" is missing data i was looking at the is.na(xx) <- c(..,...,) idea but i can't seem to apply it properly, can anyone offer advice? On a side issue while i'm

Dear all, Could any one please tell me the exact formula R uses to calculate the sample size for one-sample and two-sample t-tests? Thanks, Caimiao [[alternative HTML version deleted]]

Hi Tobias and Sven, Thanks for your discussion and suggestion. @Sven: ISL actually allows users to have different identifiers with the same name. The problem that we have discussed is caused by incorrect usage of isl_space in Polly, so please do not worry about ISL library. You can skip the following information related to Polly implementation. @Tobias and Polly developers: I have attached

On 07/28/2013 06:52 AM, Star Tan wrote: > Hi Tobias, > > I tried to investigated the problem related to ScopInfo, but I need your > help on handling some problems about ISL and SCEV. I copied the list as the discussion may be helpful for others. @Sven, no need to read all. Just search for your name. [..] >>The interesting observation is, that Polly introduces three parameters

Full_Name: alex Version: 2.8.1 OS: Ubuntu / MacOSX Submission from: (NULL) (162.38.183.51) > 0.6==0.6 [1] TRUE > seq(0,1,0.1)==0.4 [1] FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE > seq(0,1,0.1)==0.6 [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE > seq(0,1,0.1)==0.8 [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE

On 07/25/2013 09:01 PM, Star Tan wrote: > Hi Sebastian, > > > Recently, I found the "Polly - Calculate dependences" pass would lead to significant compile-time overhead when compiling some loop-intensive source code. Tobias told me you found similar problem as follows: > http://llvm.org/bugs/show_bug.cgi?id=14240 > > > My evaluation shows that "Polly -

At 2013-07-26 14:14:51,"Tobias Grosser" <tobias at grosser.es> wrote: >On 07/25/2013 09:01 PM, Star Tan wrote: >> Hi Sebastian, >> >> >> Recently, I found the "Polly - Calculate dependences" pass would lead to significant compile-time overhead when compiling some loop-intensive source code. Tobias told me you found similar problem as follows:

Dear R-list members, I have a problem with translating a mathematica script into R. The whole script is at the end of the email (with initial values for easy reproduction) and can be pasted directly into R. The problematic part (which is included below of course) is <--- Original Mathematica ---> (* p_svbar *) UiA = Ni (Dsi - 2Di A + A^2)/2; UiiA = Nii (Dsii - 2Dii A + A^2)/2; psvbar =