similar to: Beginner question: Calling intrinsic

Hi John, What targer are you trying to compile this for? I imagine this is just a case of using an X86 intrinsic on a non-X86 back end. Or is this an intrinsic you added and didn't provide a selection pattern for? In any case, this intrinsic makes it into the selection DAG and the instruction selector tries to select a sequence of instructions for it. However, it fails to find a pattern that

If you are using x86, you probably need to pass something like -mcpu=haswell or -mattr=bmi2 to enable support for the intrinsic. It seems to -mcpu=native doesn't work for lli so it can't just autodetect your CPU. ~Craig On Sun, Jan 7, 2018 at 7:54 AM, Nemanja Ivanovic via llvm-dev < llvm-dev at lists.llvm.org> wrote: > Hi John, > What targer are you trying to compile this

I have a group of students working with me on some LLVM projects related to our Parabix research. One interesting issue that has come up for us is code generation support for the Haswell new instructions pext and pdep. These instructions shuffle bits within a 64-bit word, either gathering all selected bits to the beginning (pext) or scattering some initial bits throughout (pdep). A natural

I am doing a reanalysis of results that have previously been published. My hope was to demonstrate the value of adoption of more modern regression methods in preference to the traditional approach of univariate stratification. I have encountered a puzzle regarding differences between I thought would be two equivalent analyses. Using a single factor, I compare poisson models with and without

Hi I was wondering if there is a permutation test available in R for linear models with continuous dependent covariates. I want to do a test like the one shown here. bmi<-rnorm(100,25) x<-c(rep(0,75),rep(1,25)) y<-rnorm(100)+bmi^(1/2)+rnorm(100,2)*x+bmi*x H0<-lm(y~1+x+bmi) H1<-lm(y~1+x+bmi+x*bmi) anova(H0,H1) summary(lm(y~1+x+bmi)) But I want to use permutation testing to

Im doing a project using Rcommander. I have a dataset with 5 variables, BMI being one of them. I would like to find the variance, standard deviation, range, median, etc of BMI. However, everytime I type a command into the script window, (such as var(BMI$BMI,na.rm=TRUE) )an error message pops up saying Object "BMI" not found. I can graph it, work it, do t-test, etc,. It's listed as

Hello, Say I have 2 columns, bmi and gender, the first being all the values and the second being male or female. How would I subset this into males only and females only? I have searched these fora and read endlessly about select[] and split() functions but to no avail. Also the table is not ordered. bmi gender -> bmi gender + bmi gender 1 24.78 male

hi everyone, wondering if you could help me with a novice problem. I have a data frame called subjects with a height and weight variable and want to calculate a bmi variable from the two. i have tried: attach(subjects) bmi <- (weight)/((height/100)^2) but it comes up with the error: Warning messages: 1: In Ops.factor(height, 100) : / not meaningful for factors 2: In Ops.factor((weight),

Dear R-helpers, First I apologize if my question is quite simple I have a large datasets which more 100 variables. For a research I need to change all name of variables with add one or more letters on each variables. For example, > data(Pima.tr) > Pima.tr[1:5,] npreg glu bp skin bmi ped age type 1 5 86 68 28 30.2 0.364 24 No 2 7 195 70 33 25.1 0.163 55 Yes 3 5

Hola a todos, -Estoy estudiando el efecto de dos genotipos (~tratamientos) en la aparición de síndrome metabólico (MetS) con datos longitudinales recogidos a tiempo 0,7,10,15,20 y 25 años. -He hecho un dataframe con las siguientes variables MetS: Síndrome Metabólico (Si=1,No=0) bmi: Indice de masa corporal (IMC) cuando se produce la conversión a MetS+ . Para los que permancen MetS-, esta variable

Hello, I'm not sure if I'm in the right place with my question... I'm running R on Windows and wrote a function and saved it as .R file. It looks like this: bmi <- function(weight, height) { bmi <- weight / height^2 bmi } If I want to use this function, I have to mark everything and then press Ctrl-R. But then everything single line is executed on the command line,

Hi All, I have a small dataset named das (43 cases) in which I am trying to create a binary outcome (1/0) based on the following code: if (das$age>65 && das$bmi>30) {das$danger<-1} else das$danger<-0 I am setting a flag called 'danger' to 1 of the subject is over 65 and has a BMI > 30. I find that my statement evaluates the first record in the data.frame and

Hello I would like to pass a model formula as an argument to the with.mids function from the mice package. The with.mids functon fits models to multiply imputed data sets. Here's a simple example library(mice) #Create multiple imputations on the nhanes data contained in the mice package. imp <- mice(nahnes) #Fitting a linear model with each imputed data set the regular way works

Hello, How would you go about handling the following situation? This is on R 2.12.0 on Ubuntu 32-bit. I have a wrapper function to lm. I want to pass in a subset argument. First, I just thought I'd use "...". ## make example reproducible set.seed(123) df1 <- data.frame(age = rnorm(100, 50, 10), bmi = rnorm(100, 30, sd = 2)) ## create a wrapper using

Hello, If you want to bootstrap a statistic, I suggest you use base package boot. You would need the data in a data.frame, see how you could do it. library(boot) bootMedianSE <- function(data, indices){ d <- data[indices, ] fit <- rq(crp ~ bmi + glucose, tau = 0.5, data = d) ypred <- predict(fit) y <- d$crp median(y - ypred)^2 } dat <-

Hi:   I am using the following code to read a data set in txt in R and using the follwoing model. But it seems to give me an error ' expected variable name error pos 134022'. Any help is greatly appreciated.   Code: anal.data <- read.table("nausea.txt", header=T, sep="\t") list(names(anal.data)) attach(anal.data) n.samples <- dim(anal.data) [1] # number of data

I forgot, you should also set.seed() before calling boot() to make the results reproducible. Rui Barradas On 5/22/2018 10:00 AM, Rui Barradas wrote: > Hello, > > If you want to bootstrap a statistic, I suggest you use base package boot. > You would need the data in a data.frame, see how you could do it. > > > library(boot) > > bootMedianSE <- function(data,

Dear R-experts, I am trying to bootstrap (and average) the median squared error evaluation metric for a robust regression. I can't get it. What is going wrong ? Here is the reproducible example. ############################# install.packages( "quantreg" ) library(quantreg) crp <-c(12,14,13,24,25,34,45,56,25,34,47,44,35,24,53,44,55,46,36,67) bmi

Hi: I loaded the LARS package,and input: data(diabetes),load the embedded data then I found the varialbes are in this form: x.age,x.bmi......(10 of them),X2.age,X2.bmi....(64 of them) When I input x,R gave me all 10 varialbes,and input X2,it gave me 64 variables,but if I input x.age,it returned nothing,I wonder how to affiliate those subvariable such as x.age,x.bmi to x,since I

Hello everyone, I have a data set that contains characteristics of 25,000 patients of 92 different hospitals. I have run a regression to capture the probability these patients will have a complication after a certain operation. Now, I actually want to predict the probability per patient, using the outcome of the regression, but I just certain patients involved in the prediction. So, I want to use