similar to: R extract vertices for polygon

Hello there, I'm still struggling with the *apply commands. I have 5 people with id's from 10 to 14. I have varying amounts (nrep) of repeated outcome (value) measured on them. nrep <- 1:5 id <- rep(c("p1", "p2", "p3", "p4", "p5"), nrep) value <- rnorm(length(id)) I want to create a new vector that contains the sum of the

Dear all, I am a newbie in R and could not find help on this problem. I am trying to plot an histogram with probabilities in the y axis. This is the code I am using: #TLC uniform n=30 mi=1; mx=6 nrep=1000 xbar=rep(0,nrep) for (i in 1:nrep) {xbar[i]=mean(runif(n,min=mi,max=mx))} hist(xbar,prob=TRUE,breaks="Sturges",xlim=c(1,6),main=paste("n =",n), xlab="Média",

hi im a bioinformatics student as i have never had any previous programming experience i need help this is the question i need to answer: Random walk model we want to model a random walk where you take a step to the left with probability p and one to the right with probability 1-p. Now assume that there is a line of 11 squares. once you are in square 0 or in square 10 the walk ends. The aim

R-users, I can't tell what's causing the following error. The vignette does not make a reference to a "packages" option or parameter. > library(MonteCarlo) Loading required package: abind Loading required package: codetools Loading required package: rlecuyer Loading required package: snow Loading required package: snowfall > infest_kud_fun<-function(x,A,B){ +??

Full_Name: Nuno Monteiro Version: 2.3.1 OS: Windows XP HE Submission from: (NULL) (84.9.38.207) I'm using the FEAR library to perform Data Envelopment analysis with a 36,000 obs dataset. The function dea is working fine but then when I try to use the boot.sw98 to come up with some sensitivity analysis I get the following error:

A larg program which worked with lme4/R about a year ago failed when I re-run it today. I reproduced the problem with the program below. -- When lme4 is not loaded, the program runs ok and fast enough -- When lme4 is loaded (but never used), the do.call fails with infinite recursion after 60 seconds. Memory used increases beyond bonds in task manager. -- I tested a few S3 based packages

A larg program which worked with lme4/R about a year ago failed when I re-run it today. I reproduced the problem with the program below. -- When lme4 is not loaded, the program runs ok and fast enough -- When lme4 is loaded (but never used), the do.call fails with infinite recursion after 60 seconds. Memory used increases beyond bonds in task manager. -- I tested a few S3 based packages

This looks like the sort of thing that you should ask the package maintainer (?maintainer). Cheers, 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 ) On Thu, Feb 15, 2018 at 11:39 AM, john polo <jpolo at mail.usf.edu> wrote: >

I am using bootstrap and cannot figure how to tell R to ignore missing values (NA) I tried this syntax and it did not work. The name of the file is banks the column two. bootmean(banks$two,na.rm = True, conf = 90,nrep = 1000) -- View this message in context: http://r.789695.n4.nabble.com/Missing-Values-tp4643059.html Sent from the R help mailing list archive at Nabble.com.

Hi - Writing to see if someone can suggest whether a problem warrants a bug report. It concerns the use of stepFlexclust in the flexclust package. The problem concerns the size of clusters returned. Versions: R-2.7.0 on Windows XP; RODBC_1.2-3 code snippet: r8 <- stepFlexclust(df,8,nrep=100,FUN=kcca, family=kccaFamily("kmedians")) summary(r8) ## returns cluster sizes of 51, 115,

Dear R users, i have a matrix with 31 rows and 444 columns and i want to extract every 37th column of that matrix starting from 1. more precisely i want to select columns 1, 38,75, 112 and so on. then doing the same by starting from column number 2(2,39,76,113.......). i know that there is a manual way of doing it but i wanted to make it more quickly as i have fairly large data to dealth with.

Hi, I am fairly new to R and have encountered an issue with the lmRob function that I have been unable to resolve. I am trying to run a robust regression using the lmRob function which runs successfully, but the results are rather strange. I'm not sure it's important, but my model has 3 dichotomous categorical variables and 2 continuous variables in it. When I look at a summary of my

Hi all-- We are planning an intervention study for adolescent alcohol use, and I am planning to use simulations based on a hurdle model (using the hurdle() function in package pscl) for sample size estimation. The simulation code and power code are below -- note that at the moment the "power" code is just returning the coefficients, as something isn't working quite right. The

Hello, I've put the short version here and if anyone wants to run the code with CollocInfer, I've given the full version in the file "analysis". I come at the question of array attributes and dimnames to try to simplify. In a CollocInfer LS.profile analysis using this array 'Y' constructed as follows: w=rnorm(41,.05) z=rnorm(41,.06) yX<-cbind(w,z)

Good Morning: I posted an initial question a few days ago and I received some good advice from two R experts. I have re-examined the Davison-Hinkley text paying close attention to the examples of the boot() and boot.ci() in that text and the single example of a similar process in the MASS book (not the MASS package manual as I initially misunderstood). I think I understand how the stratified

Dear experts, I am a beginner of R. I'm looking for experts to guide me how to do programming in R in order to randomly replace 5 observations in X explanatory variable with outliers drawn from U(15,20) in sample size n=100. The replacement subject to y < 15. The ultimate goal of my study is to compare the std of y with and without the presence of outliers based on average of 1000

Hi everybody, while performing ks.test for a standard exponential distribution on samples of dimension 2500, generated everytime as new, i had this strange behaviour: >data<-rexp(2500,0.4) >ks.test(data,"pexp",0.4) One-sample Kolmogorov-Smirnov test data: data D = 0.0147, p-value = 0.6549 alternative hypothesis: two.sided >data<-rexp(2500,0.4)

Hi, I am running some latent class models with civariates using poLCA in R, and have a question the meaning of some error messages. My model has 8 y-variables (dichotomous) and 2 x-variables (also dichotomous), and I am trialling different numbers of classes. When I run a 2-class model, the model runs fine without any error messages. I used the nrep = 10 option to avoid local maxima. Class %

Greetings: In R parallel's vignette, there is a comment "It would however take only slightly more work to allocate a stream to each task." (p.6). I've written down a working example that can allocate not just one, but several separate seeds for each task. (We have just a few project here that need multiple streams). I would like to help work that up for inclusion in the

Dear Contributors, thanks for collaboration. I am trying to reorganize data frame, that looks like this: n1.Index Date PX_LAST n2.Index Date.1 PX_LAST.1 n3.Index Date.2 PX_LAST.2 1 NA 04/02/07 1.34 NA 04/02/07 1.36 NA 04/02/07 1.33 2 NA 04/09/07 1.34 NA 04/09/07