similar to: How to turn individual consecutive information into survival objects?

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

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 Tobias and all LLVM/Polly developers, Thank you very much for all your help and advice. I have submitted my proposal to GSoC 2013 application system: http://www.google-melange.com/gsoc/proposal/review/google/gsoc2013/star/1. Some tables and paragraphs are simplified to make it more readable on GSoC official pages. Any suggestion or comment would be appreciated. At 2013-05-03

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.

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

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

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

Hello, i wrote this function guete and now i want to plot it: but i get this error message. i hope someone can help me. Error in dim(robj) <- c(dX, dY) : dims [product 16] do not match the length of object [1] p_11=seq(0,0.3,0.1) p_12=seq(0.1,0.4,0.1) guete = function(p_11,p_12) { set.seed(1000) S_vek=matrix(0,nrow=N,ncol=1) for(i in 1:N) { X_0=rmultinom(q-1,size=1,prob=p_0)

Full_Name: Manuel Luethi Version: 2.9.1 OS: Windows XP Submission from: (NULL) (129.132.128.136) Hi I created the following vectors: p_1=c(0.2,0.2,0.2,0.2,0.1,0.25,0.4,0.1,0.25,0.4,0.1,0.25,0.4,0.1,0.25,0.4,0.2,0.5,0.8,0.2,0.5,0.8,0.2,0.5,0.8,0.2,0.5,0.8) p_2=c(0,0,0,0,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.4,0.25,0.1,0.4,0.25,0.1,0.4,0.25,0.1,0.4,0.25,0.1) As these are

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)

Hi, Does R have any functions implementing such multinomial regression: (S_t^A,S_t^B)~MN(N_t-Y_{t-1},P_t^A,P_t^B) where MN(n,p_1,p_2) is multinomial distribution with parameters n, p_1, p_2. Here P_t^A and P_t^B are nonlinear functions from predictor variables and parameters which need to be estimated. Here A and B are used for notation, they are not parameters. My second question is about

hi, i'm really in trouble to simulate some experiment. that is, it takes too much time to process the following code. following is short example, ------------------------------------------------------------------------------------------------------- p<-data.frame(a=rnorm(10),b=rnorm(10),c=rnorm(10),d=rnorm(10)) test<-data.frame(a=rnorm(1),b=rnorm(1),c=rnorm(1),d=rnorm(1))

I am trying to make the following Kalman filter equations work and therefore produce their graphs. v_t=y_t - a_t a_t+1=a_t+K_t*v_t F_t=P_t+sigma.squared.epsilon P_t+1=P_t*(1-K_t)+sigma.squared.eta K_t=P_t/F_t Given: a_1=0,P_1=10^7,sigma.squared.epsilon=15099, sigma.squared.eta=1469.1 I have attached my code,which of course doesnt work.It produces NAs for the Fs,Ks and the a. Can somebody tell me

2009/8/30 Uwe Ligges <ligges at statistik.tu-dortmund.de>: [snip] > Guido van Steen wrote: [snip] >> Something that interests me too: What about R's policy with respect to >> including binary files? I saw that developers should include a file [snip] > Please do not include binary files and carefully watch for licenses of those > files (e.g. if GPL'ed, you need to

Saludo cordial para cada uno. Les pido ayuda para generar números aleatorios de una mixtura k-puntos. Sabemos que la función de distribución F es una mixtura k-puntos si es de la forma F(x) = p_1 F_1(x) + p_2 F_2(x) + … + p_k F_k(x), donde F_j es una función de distribución de probabilidad, p_j > 0 y suma(p_j) = 1, para j = 1, 2, …, k. En mi caso particular F es la suavización de la

Hi, I am trying to use existing C++ code from R. I have no problems compiling C code and using it in R, but with C++ I'm running into problems. Here's the compiler output: Macintosh-10:~/Desktop/dissertation/Model - CPP version/R labguest$ g++ -I/Library/Frameworks/R.framework/Resources/include -I/Library/Frameworks/R.framework/Resources/include/i386 *.cpp In file included from

Hola! I have a problem which is not strictly R, although R will be used for the analysis. We have data from a large investigation of drug abuse, initially analyzed by logistic regression. But the pupils are selected by first sampling schools, and as it happens the prevalence of use varies sharply from school to school, so there is over-dispersion. Now we are interested in comparing the