similar to: [LLVMdev] Strange code generation issue

On 23 February 2015 at 01:29, Kamal Sharma <kgs1.rice at gmail.com> wrote: > Hi Dibyendu, > > It would be very helpful if you could post the original source code or > snippet. > That way, one can investigate deeper to understand the problem. > > Regards, > Kamal Sharma > Hi Kamal, Sure. I guess I ought to create a test that one can look in isolation. I am

On 22 February 2015 at 20:58, David Jones <djones at xtreme-eda.com> wrote: > Not sure if this is your problem, but it was mine: > > You must create (or obtain) a DataLayout *and install it into the Module*. > > It is possible to generate machine code for IR and not install the > DataLayout into the Module. Rather, the DataLayout is used locally at the > point where code

Hi, I am generating following code: %base = getelementptr inbounds %ravi.CallInfo* %6, i32 0, i32 4, i32 0 %7 = load %ravi.TValue** %base %8 = bitcast %ravi.TValue* %7 to i8* %9 = bitcast %ravi.TValue* %5 to i8* call void @llvm.memcpy.p0i8.p0i8.i32(i8* %8, i8* %9, i32 16, i32 8, i1 false) %10 = load %ravi.CallInfo** %L_ci %base1 = getelementptr inbounds %ravi.CallInfo* %10, i32 0,

On 22 February 2015 at 22:54, Hal Finkel <hfinkel at anl.gov> wrote: >> I tried setting the module's DataLayout to the engine's DataLayout. >> Don't see any improvement. >> The memcpy() is to perform a struct assign, so I tried replacing that >> with member by member store. >> But even then the loads are not being eliminated so I guess the >>

I am writing a resampling program for multiple regression using lm(). I resample the data 10,000 times, each time extracting the regression coefficients. At present I extract the individual regression coefficients using brg = lm(Newdv~Teach + Exam + Knowledge + Grade + Enroll) bcoef[i,] = brg$coef This works fine. But now I want to extract the t tests on these coefficients. I cannot

Hi R users, I have a very large data set that has two conditioning variables for the test I want to perform. A toy set can be simulated: type<-sample(1:3,100,replace=TRUE) class<-sample(1:20,100,replace=TRUE) value<-rnorm(100) data<-cbind(type,class,value) (though type and class are alphanum) I want to perform the three pair-wise t-tests between types for each class in data. Can

I?ve been struggling with seemingly ?corrupt? data.frames for a few days, and believe I?ve narrowed the problem down to some odd behaviour from read.table I receive a tab delimited file from an external provider where strings are encoded as =?content?. Not sure why, perhaps as most users open it in Excel. My specific issue is that trailing spaces in any of the strings are causing strange results

Hi all, I am a newbie of R, and have a very simple question. When I run the following t test result = t.test(weight ~ group) If I want to get the t value, I can do tvalue = result$statistic with tvalue being the following: t 1.191260 However, if I just want the number 1.191260, not the character "t", how can I achieve that? Thank you very much, Gang

Hello. How can I compute the Bootstrap p-Value for a one- and two sided test, when I have a bootstrap sample of a statistic of 1000 for example? My hypothesis are for example: 1. Two-Sided: H0: mean=0 vs. H1: mean!=0 2. One Sided: H0: mean>=0 vs. H1: mean<0 I hope you can help me Thanks in advance Regards, Andreas

Hi everyone, If I compute a "Ordered Logistic or Probit Regression" with the polr function from MASS package. the summary give me : coefficients, Standard error and Tvalue.. but not directly the p.value. I can compute "manualy" the Pvalue, but Is there a way to directly obtain the pa.value, and I wonder why the p.valeu is not directly calculated, is there a reason? exemple

Hi all, I want to make the following: I want to run a linear regression on each column of a matrix "estima" on the correspondent column on the matrix "estima2". You see I want to regress estima[,1] on estima2[,1] this way to all columns.... At the same time I want to make a regression adding each time a new observation. You see, the first regression will regress only one

Hi All, I'm fitting an proportional odds model using vglm() from VGAM. My response variable is the severity of diseases, going from 0 to 5 (the severity is actually an ordered factor). The independent variables are: 1 genetic marker, time of medical observation, age, sex. What I *need* is a p-value for the genetic marker. Because I have ~1.5 million markers I'd rather not faffing

Hi all R-users, I?m trying to assign colors on those p-value in my table output that fall above a certain critical value, let?s say a p-value >0.05. My table looks like this: Assets ADF-Level P-Value ADF-First D P-Value ADF-Second D P-Value [1,] Liabilities -2.3109 0.1988 -3.162 0.025 -6.0281

In the model: lm.1 <- lm(variable ~ BLOC + TIL * YEAR , data=selvanera) I found TIL*YEAR interaction significant. Then I am trying to compare means of the different levels of TIL inside every YEAR using: mc.2 <- glht(lm.1, linfct = mcp(TIL*YEAR="Tukey")) summary(mc.2, test = univariate()) but it does not work. There is any way of doing this, like the SLICE option in

I have a matrix which I wanted to convert to a data frame. As I could not succeed and resorted to export to csv and reimport it again. Why did I fail in the attempt and how can I achieve what I wanted without this roundabouts? The original matrix: > str(comb_model0) num [1:90, 1:4] 3.5938 0.0274 0.0342 0.0135 0.0207 ... - attr(*, "dimnames")=List of 2 ..$ : chr [1:90]

Hello, As a new user of R (less than a month) I have got my hands on several books and am pouting through the net looking for help in gaining understanding of this powerful tool. I am becoming more proficient with using basic functions to conduct basic statistics. I am now looking to learn how to write code. After a few small worthless functions I decided to try to create a function that was

Hello R-Experts, I've got a question, concerning the automation of a number of regressions (lm) with the help of a loop (for i in ....). The situation is as follows (the code follows after that): I have my data in an access database. I have historical data for 2000 parts, for each of this parts I want to do a regression analysis, so I need to do 2000 regressions (just for one country, there

How do we get 2-tailed p-values for the rlm summary? I'm using the following: > fit <- rlm(oatRT ~ oatoacData$erp, psi=psi.bisquare, maxit=100, na.action='na.omit') > fitsum <- summary(fit, cor=F) > print(fitsum) Call: rlm(formula = oatRT ~ oatoacData$erp, psi = psi.bisquare, maxit = 100, na.action = "na.omit") Residuals: Min 1Q Median

Hi, I want to write the summary from a regression. I am doing this because I do not see a way of get the std error, tvalues from the coefficients diagnostic. n$coef does not give this only get the intercept and slope. I tried to use write and write.table and got error in both cases. I jumped thru the hoops below to no avail. Also note, this is in windows. I used to use unix, and do not

I am trying to pass an equation as an arguement to a function, which seems pretty straightforward given lazy evaluation. I constructed the following little test to make sure I sort of knew what I was doing: go <- function(X,eq) { C <<- X*2; d <<- eq} a _ rnorm(100) go(10,eq=a[.5*length(a)]+C+1) > C [1] 20 > d [1] 21.10551 > a[.5*length(a)] [1] 0.1055086 Everything