similar to: Suggestions to speed up median() and has.na()

Motivated by Deepayan's recent inquiries about the efficiency of the R 'quantile' function: http://tolstoy.newcastle.edu.au/R/devel/05/11/3305.html http://tolstoy.newcastle.edu.au/R/devel/06/03/4358.html I decided to try to revive an old project to implement a version of the Floyd and Rivest (1975) algorithm for finding quantiles with O(n) comparisons. I used

Hi everyone, I ve been using R for months and find it really practical and straight forward. However (the inevitable however), I am finding it very slow for one of my operations: it s basically an itertation over i and j in a pretty big table (4* 4608). It takes 30 minutes!!!! Thanks Ps:if it can help here is the source: median1<-matrix(nrow=4608,ncol=1)

I sent the message below to r-sig-mac yesterday, but having no reply I decided to explore a bit myself and found that editing: /Library/Frameworks/R.framework/Versions/2.3/Resources/share/make/ shlib.mk yzzy: diff shlib.mk shlib.mk~ 3c3 < include $(R_HOME)/etc/Makeconf --- > include $(R_HOME)/etc${R_ARCH}/Makeconf restored the functionality of R CMD INSTALL. Is this a known issue?

Hi, I was wondering whether there is any Fortran function or associated library for evaluating the quantiles of a set of values (something which the R-function quantile() does). Any help will be much appreciated. Thanks and regards, Dhiman Bhadra [[alternative HTML version deleted]]

Hi there, I got a data frame with more than 200k columns. How could I get median of each column fast? mapply is the fastest function I know for that, it's not yet satisfied though. It seems function "median" in R calculates median by "sort" and "mean". I am wondering if there is another function with better algorithm. Any hint? Thanks, Xin Zheng

Hi, This is essentially a reposting of http://tolstoy.newcastle.edu.au/R/devel/05/11/3305.html which had no responses, and the behaviour reported there persists in r-devel as of yesterday. (1) sort() with non-null partial > x = rnorm(100000) > keep = as.integer(ppoints(10000) * 100000) > system.time(sort(x)) [1] 0.05 0.00 0.04 0.00 0.00 > system.time(sort(x, partial = keep)) [1]

With this example set.seed(123) A <- matrix(runif(40), nrow = 8) y <- 1:nrow(A) A.laqr <- qr(A, LAPACK=TRUE) both qr.qy(A.laqr,y) and qr.qty(A.laqr,y) give the respective error messages Error in qr.qy(A.laqr, y) : 'b' must be a numeric matrix Error in qr.qty(A.laqr, y) : 'b' must be a numeric matrix However when Lapack is not used as in A.liqr <- qr(A,

... and the mailing list is picky about attachments... whatever you attached did not conform to the stringent requirements mentioned in the Posting Guide. Pasting the code right into the email is usually safest, though you DO have to post using plain text (as the Posting Guide indicates) or your code may get mangled by the automatic html format removal. On May 15, 2018 7:04:31 AM PDT, Bert Gunter

OK, Let's try this again! Here is the reproducible script; it is long because I had to copy the panel dataset here. My question is related to systemfit; I don't know how to get the result for the entire panel. #Reproducible script Empdata<- read.csv("/Users/ngwinuiazenui/Documents/UPLOADemp.csv") View(Empdata) install.packages("systemfit")

Unless there is good reason not to, always cc the list -- there are lots of smarter folks than I on it who can help. I may or may not have time to look at this. Hopefully someone else will. -- Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip

Sadly you failed to set your email program to send plain text and the data is corrupted at my end. I also think you need to reduce the size of the data set... the intent here is to increase your understanding, not debug your particular analysis. I will say that I am having a very challenging time understanding what you are trying to accomplish though. What are the equations that you think need

I can't get my simultaneous equations to work using system fit. Please help. #Reproducible script Empdata<- read.csv("/Users/ngwinuiazenui/Documents/UPLOADemp.csv") View(Empdata) str(Empdata) Empdata$gnipc<-as.numeric(Empdata$gnipc) install.packages("systemfit") library("systemfit") pdata <- plm.data(Empdata,

Hi there, I have a large amino acid csv file like this: input.txt: P,LV,Q,Z P,VL,Q,Z P,ML,QL,Z There is a problem with this file, since LV and VL are in fact the same thing. How do I order each element according to alphabetical order so that the desired output would look like: output.txt: P,LV,Q,Z P,LV,Q,Z P,LM,LQ,Z -- View this message in context:

Dear all, from the help page of quantile: "x ??? numeric vectors whose sample quantiles are wanted. Missing values are ignored." from the help page of IQR: "x ??? a numeric vector." as a matter of facts it seems that both quantile() and IQR() do not check for the presence of a numeric input. See the following: set.seed(11) x <- rbinom(n=11,size=2,prob=.5) x <-

dear group, i have 100 files starting with 'hsa-*'. ex. file: fruit p-value ------------ apple 0.0003 orange 0.004 kiwi 0.0003 peach 0.0004 I want to read all these files and create a single matrix. here each file may have different fruit names. in the matrix i want to have a union of all fruits and those should be the rows in the matrix and file names should be columns.

Hi, I tried looking through google search on whether there's a way to computer the median for each row of a nxn matrix and return the medians for each row for further computation. And also if the number of columns in the matrix are even, how could I specify which median to use? Thank you very much! -- Edward Chen [[alternative HTML version deleted]]

Hi R user I need to read in some values from a computer program output. I can't change the output format because the developer of the program doesn't allow to change the format of output. There are two formats. First one looks like this if I have 10 variables, ------------------------------------------------------------------------------------------------------ [ 1]

Is there a weighted median function out there similar to weighted.mean() but for medians? If not, I'll try implement or port it myself. The need for a weighted median came from the following optimization problem: x* = arg_x min (a|x| + sum_{k=1}^n |x - b_k|) where a : is a *positive* real scalar x : is a real scalar n : is an integer b_k: are negative and positive scalars

Hello, I need help to understand my error in this code... I would like to make a direct sampler... thanks Celine p<-matrix(c(1,2,3,2,1,4),3,2,byrow=T) p<-p/sum(p) ky<-ncol(p) kx<-nrow(p) p.vec<-as.vector(t(p)) l<-rmultinom(1,1,p) l<-(t(l)) m<-(l%%ky) ifelse (m==0, i<-l/ky && (j<-ky), i<-((l/ky)+1) && (j<-(l %% ky)

Hello, all, I have a dataframe of three rows and umpteen columns. I want to show the maximum, minimum, and median with a vertical line and a central dot (I'd use a boxplot, but with only three data points, that's overkill; I can't just use points, because of overlap and some of the other data plotted on the graph). This works: > boxplot(data_frame,