similar to: Quantiles of a subset of data

I have written a function that goes through a database and calculates various metric scores and allocates them to a data set. For 400 of the 500 sites that I calculate these metrics for works fine and allocates the scores into the appropriate column. For some reason, some sites I run into the below problem: Here is what I am doing: > names(orig.metric) [1] "BenInsect"

Hi, I need to addDestination to some basic blocks I used the following code Value* Address; IndirectBrInst *IBI = IndirectBrInst::Create(Address, Result.size(),i->getTerminator() ); IBI->addDestination(i); The following error was issued void llvm::IndirectBrInst::init(llvm::Value *, unsigned int): Assertion `Address && Address->getType()->isPointerTy() &&

Hi All, I installed qcc package and the dependency packages. For the first time I can use the function : process.capability.sixpack(). But later when ran the code again I always got the following error: Error: could not find function "process.capability.sixpack". I tried reinstalling the qcc package but didn't help. Does anyone have this kind of experience? Thank you! Regards, Yan

Hi 1- for(rit=Result.begin();rit!=Result.end();++rit) { Value* Address= BlockAddress::get (*rit); IndirectBrInst *IBI = IndirectBrInst::Create(Address, Result.size(),i->getTerminator() ); IBI->addDestination((*rit)); } I tried this code , but the needed destination wasn't added. 2- About LLVM backend $ llc -march=cpp example_file.ll -o I think it

Greetings, I am having a problem with DescTools::Quantile (a function computing quantiles from weighted samples): # these sum to one probWeights = c( 0.0043, 0.0062, 0.0087, 0.0119, 0.0157, 0.0204, 0.0257, 0.0315, 0.0378, 0.0441, 0.0501, 0.0556, 0.06, 0.0632, 0.0648, 0.0648, 0.0632, 0.06, 0.0556, 0.0501, 0.0441, 0.0378, 0.0315, 0.0257, 0.0204, 0.0157, 0.0119, 0.0087,

Hi Rasha, > I need to addDestination to some basic blocks Just to make sure there's no confusion here: you really are trying to create code like: define i32 @foo(i1 %tst) { %Address = select i1 %tst, i8* blockaddress(@foo, %true), i8* blockaddress(@foo, %false) indirectbr i8* %Address, [label %true, label %false] ; This is what you're creating true: ret i32 42 false: ret i32

1- I need the first example. 2- I set the Address uninitialized according to the documentation " Setting the name on the Value automatically updates the module's symbol table" from Value.h source code 3- I'm not sure about "select" instruction, you mean that the address is the new destination (basic block)that will be added Thanks On 23 July 2013 16:38, Tim Northover

I have 20 variables: 5,9,6,1,5,9,7,4,5,6,3,2,4,8,9,6,1,8,4,8 How do I calculate the corresponding quantiles from a normal distribution with the same mean and variance as the sample? Also, how do I draw a QQ plot of the data? Thanks for any help! -- View this message in context: http://www.nabble.com/Quantiles-and-QQ-plots-tf4925742.html#a14097909 Sent from the R help mailing list archive at

Hi, I'm working on a data set that contains a couple of factors and a number of dependent variables. From all of these dependent variables I would like to calculate mean, standard deviation and quantiles. With the function FUN I get all the means and stdev that I want but quantiles are only calculated for the first of the dependent variables (column 8 in the summarize command). What do I

Dear List, quantile(x) function allows to obtain specified quantiles of a vector of observations x. Is there an analogous function to compute quantiles in the case one have the vector of the observations x and the correspondent vector f of relative frequencies ? Thank you Paolo Radaelli [[alternative HTML version deleted]]

I have a set of values and their corresponding weights. I can use the function weighted.mean to calculate the weighted mean, I would like to be able to similarly calculate the weighted median and quantiles? Is there a function in R that can do this? thanks, Spencer [[alternative HTML version deleted]]

Hi, I guess that my problem has an obvious answer, but I have not been able to find it. Suppose I create a custom function, consisting of two beta-distributions: myfunction <- function(x) { dbeta(x,2,6) + dbeta(x,6,2) } How can I calculate the quantiles of myfunction? I have not seen any continous function treated in the docs, and applying the "quantile function" gives me an

Dear list, I have got an array with observational values t and I would like to fit a geometric distribution to it. As I understand the geometric distribution, there is only one parameter, the probability p. I estimated it by 1/mean(t). Now I plotted the estimated density function by plot(ecdf(t),do.points=FALSE,col.h="blue"); and I would like to add the geometric distribution. This

I have summary statistics from many sets (10,000's) of near-normal continuous data. From previously generated QQplots of these data I can visually see that most of them are normal with a few which are not normal. I have the raw data for a few (700) of these sets. I have applied several tests of normality, skew, and kurtosis to these sets to see which test might yield a parameter which

Given f, a pdf over a finite interval, is there any existing R function that can efficiently tabulate the cumulative distribution function for f, or produce all N+1 quantiles of the form i/N? "Efficiently" here means better than doing repeated integrations for each point.

Dear all, I am searching for a way to compute a test comparable to Chuang et al. ("Causality in Quantiles and Dynamic Stock Return-Volume Relations"). The aim of this test is to check wheter the coefficient of a quantile regression granger-causes Y in a quantile range. I have nearly computed everything but I am searching for an estimator of the density of the distribution at several

Hi Rasha, On Wed, Jul 24, 2013 at 12:28 AM, Rasha Omar <rasha.sala7 at gmail.com> wrote: > 1- I need the first example. Oh good. > 2- I set the Address uninitialized according to the documentation > " Setting the name on the Value automatically updates the module's symbol > table" from Value.h source code That's referring to a string name, and is only really

I have a quick question which is very simple but I seem to have a mental block! I'm using the pchisq function to specify a Chi Squared distribution with 9 df which I'm then going to use in the Kolmogorov-Smirnov Test to test some simulated values. so simply: pchisq(q, df=9) I know that q is the vector of quantiles but could anybody tell me what exactly this vector needs to contain?

Hi All, very new to the linux thing. I have tried our local linux list but no luck. I have setup Samba on the box which is running Rh7.3 with Samba 2.2.3a-6 (server/common & client) I got a tut from IBMs site on how to setup a pdc with samba and redhat. I followed the tut step for step but still when I want to login on wind98 onto the box I get a message that the pdc is not found. When I

I am using the package Design for survival analysis. I want to plot a simple Kaplan-Meier fit of survival vs. age, with age grouped as quantiles. I can do this: survplot(survfit(Surv(time,status) ~ cut(age,3), data=veteran) but I would like to do something like this: survplot(survfit(Surv(time,status) ~ quantile(age,3), data=veteran) #will not work ideally I would like to superimpose