similar to: Hmisc label function applied to data frame

While looking at what llvm writes for this testcase, I noticed that there is one redundant operation in resulting assembly. The second 'cmp' operation there is essentially identical to the first one, with reversed order of arguments. Therefore, it is not needed. This testcase is a simple integer comparison routine, similar to what qsort would take to sort an integer array. I think

When I try running one llvm function in JIT without optimization I get SEGV. Looking at assembly (below) I see that the local value 0xffffffffffffffe0(%rbp) is used without being ever initialized (see my comment in asm). Same code on i386 works fine, with and w/out optimization. My guess is that this is a bug in LLVM. Yuri --- llvm --- %struct.mystruct = type { i32, i8, i8, i8, i8 } define

Dear R users, I am not good in R-language programming. So, i need your help. I want to convert my lower-triangle value of symmetry matrix into a vector with their row and column name. I found a function called "sm2vec" in "corpcor" package but it give only a vector of values but not row and column names. But i also want ROW and COLUMN name together with their corresponding

On Jan 11, 2011, at 4:50 PMPST, Yuri wrote: > When I try running one llvm function in JIT without optimization I get > SEGV. Looking at assembly (below) I see that the local value > 0xffffffffffffffe0(%rbp) is used without being ever initialized (see my > comment in asm). > Same code on i386 works fine, with and w/out optimization. > > My guess is that this is a bug in

Hello, I got a little interogation about these 3 points. I want to write something like this sample in my extension.conf. I have tested and it works but I don't know if it is a good way to make a menu. I don't want to put number as it is boring to maintain. Does anyone know if there is some problem to write like this? exten => 7890,1,Wait(1) exten =>

Hi All. I'd like to generate a sample of n observations from a k dimensional multivariate normal distribution with a random correlation matrix. My solution: The lower (or upper) triangle of the correlation matrix has n.tri=(d/2)(d+1)-d entries. Take a uniform sample of n.tri possible correlations (runi(n.tr,-.99,.99) Populate a triangle of the matrix with the sampled correlations Mirror the

Hi, I'm trying to obtain confidence intervals for auto and cross correlation estimates. I've adapted code made available by Stock and Watson that uses the Bartlett Kernel and the delta method. In R it runs really, really slow because of the loops it uses and I have 9 series that I'd like to examine (81 total combinations). It was easy enough to replace one of the while loops with a

Hi I'm trying to write a generic script for processing some data which finishes off with some plots. Given Im never sure how many columns will be in my dataframe I wanted to using the following plot(spectra.wavelength, cormat, type = "l", ylim=c(-1,1), xlab="Wavelength (nm)", ylab="Correlation") however even if I specify as type="l" it appears plot

Dear R users, I am trying to print heatmaps in a loop (with a pause). Idea is to visualize changing correlations over time and for testing I wrote this simple (reproducible) code below. My problem is that levelplot() does not produce any output when I run the code (though heatmap does). Ideally I would like to use levelplot() as it produces a neat index on the side indicating the color and the

Dear all, Sorry to post my query once again in the list, since I did not get attention from anyone in my previous mail to this list. Now I make it simple here that please give me a code for find out the columns of a dataframe whose correlation coefficient is below a pre-determined threshold. (For detailed query please see my previous message to this list, pasted hereunder) Thanks and regards,

Hi for the loop section runif needs curved brackets Try IAP <-NA for (i in 1:Sample.Size){ if (DataSet$SES[i]>0) { IAP[i] <- ifelse(runif(1)>0.75, 1, 0) # High SES, higher chance to be in Treatment # } else { IAP[i] <- ifelse(runif(1)<=0.25, 1, 0) # Low SES, lower chance to be in Treatment # } } # End loop # IAP IAP zjiaqi19880219 wrote > Hi,

On 10-Oct-16 06:45, Aki Tuomi wrote: > Does your build end at some particular point? See **** DETAILS **** for in depth (I hope enough!) study/report. > > Aki I would guess this is not "c99" way... Making all in lib-http source='test-http-auth.c' object='test-http-auth.o' libtool=no DEPDIR=.deps depmode=xlc /bin/sh ../../depcomp xlc_r

Newsgroup members, Does anyone have a clever way to simulate a correlation matrix such that each column contains dichotomous variables (0,1) and where each column has different prevalence rates. For instance, I would like to simulate the following correlation matrix: > CORMAT[1:4,1:4] PUREPT PTCUT2 PHQCUT2T ALCCUTT2 PUREPT 1.0000000 0.5141552 0.1913139 0.1917923 PTCUT2

Hello R-User! I appologise in advance if this should also go into statistics but I am presently puzzled. I have a data.frame (about 300 rows and about 80 variables) and my variables are dichotomous factors, continuous (numerical) and ordered factors. I would like to calculate the linear correlation between every pair of my variables, because I would like to perform a logistic regression (glm())

Dear R community,and especially Giovanni Millo, For my master's thesis i need to simulate a panel data with the fixed effects correlated with the predicor, so i run the the following code: set.seed(1970) #######################Panel data simulation with alphai correlated with xi##################################### n <- 5 t <- 4 nt <- n*t pData <- data.frame(id =

Dear R community,and especially Giovanni Millo, For my master's thesis i need to simulate a panel data with the fixed effects correlated with the predicor, so i run the the following code: set.seed(1970) #######################Panel data simulation with alphai correlated with xi##################################### n <- 5 t <- 4 nt <- n*t pData <- data.frame(id =

Dear R community,and especially Giovanni Millo, For my master's thesis i need to simulate a panel data with the fixed effects correlated with the predicor, so i run the the following code: set.seed(1970) #######################Panel data simulation with alphai correlated with xi##################################### n <- 5 t <- 4 nt <- n*t pData <- data.frame(id =

Dear R community,and especially Giovanni Millo, For my master's thesis i need to simulate a panel data with the fixed effects correlated with the predicor, so i run the the following code: set.seed(1970) #######################Panel data simulation with alphai correlated with xi##################################### n <- 5 t <- 4 nt <- n*t pData <- data.frame(id =

Hi. I am using R 2.3.1 on Windows XP. I had installed a library package into my first session and wanted the same package in my second session, so I went out to the CRAN mirror and tried to install the package, and got the following message: ********************************************************************* >utils:::menuInstallPkgs() trying URL

I am creating covariance matrices from sets of points, and I am having frequent problems where I create matrices that are non-positive definite. I've started using the corpcor package, which was specifically designed to address these types of problems. It has solved many of my problems, but I still have one left. One of the matrices I need to calculate is a cross-covariance matrix. In other