similar to: Non-R question.

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

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

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 07/25/2013 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:

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

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

Dear R List, I have a dataset with the following structure: """personal_id, p_0, p_1, p_2, .... , p_36, p_37 1, NA, 1, 4, .... , 1, NA 2, NA, NA, NA, .... , 4, NA . . . 6020, NA, 3, 3, ...., NA, NA 6021, NA, 2, 2, ...., 4, NA """ I used some made-up data. It is just meant to show the structure of the dataset. The variables of interest are p_0, ... p_37.

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

I have a simple X, Y data frame that I am trying to run regression analysis on. The linear regression looks great, but when I use lm(formula = y ~ poly(x, degree = 5)) I get the same coeffecients. So for example if I use degree =3 my formula would look like y = 4.2 x^3 + 3.2x^2 + 2.1x + 1.0 and my degree 5 would look like y = 6.5x^5+ 5.4x^4 + 4.2 x^3 + 3.2x^2 + 2.1x + 1.0, which doesn't make

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))

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

Hi all, Does anyone have an R implementation of the queplot (K.?M. Goldberg and B.?Iglewicz. Bivariate extensions of the boxplot. Technometrics, 34(3):pp. 307?320, 1992)? I'm struggling with the estimation of the asymmetry parameters. Hadley -- Assistant Professor / Dobelman Family Junior Chair Department of Statistics / Rice University http://had.co.nz/

On Wed, Apr 20, 2011 at 8:08 AM, Jianzhou Zhao <jianzhou at seas.upenn.edu> wrote: > I have a question about when we should apply these pointer aliasing > rules. Do the rules tell us when a load/store is safe? > "Any memory access must be done through a pointer value associated > with an address range of the memory access, otherwise the behavior is > undefined." >

Hi Stephan, > We are developing a bounded model checker for C/C++ programs > (http://baldur.iti.kit.edu/llbmc/) that operates on LLVM's intermediate > representation. While checking a C++ program that uses STL containers > we noticed that llvm-gcc and clang handle pointer differences in > disagreeing ways. > > Consider the following C function: > int f(int *p, int *q)

On 4/20/11 10:08 AM, Jianzhou Zhao wrote: > I have a question about when we should apply these pointer aliasing > rules. Do the rules tell us when a load/store is safe? > "Any memory access must be done through a pointer value associated > with an address range of the memory access, otherwise the behavior is > undefined." I don't think the pointer aliasing rules