similar to: Help with one of "those" apply functions

I must be reading the help file for gc() wrong. I thought it said that gc(verbose=FALSE) will run the garbage collection without printing the Ncells/Vcells summary. However, this is what I get: gc(verbose = FALSE) used (Mb) gc trigger (Mb) max used (Mb) Ncells 267097 14.3 531268 28.4 531268 28.4 Vcells 429302 3.3 20829406 159.0 55923977 426.7 I'm embedding this in an

Simply put, I want to subset the data frame 'a' where 'y=0'. > a <- as.data.frame(cbind(x=1:10, y=c(1,0,NA,1,0,NA,NA,1,1,0))) > a x y 1 1 1 2 2 0 3 3 NA 4 4 1 5 5 0 6 6 NA 7 7 NA 8 8 1 9 9 1 10 10 0 > names(a) [1] "x" "y" > table(a$y) 0 1 3 4 > table(a$y, useNA="always") 0 1 <NA> 3 4

I am trying to print a nice looking vector in Sweave. c <- 1:4 I want to see (1, 2, 3, 4) in TeX. . If I use paste(c, ",", sep="") I get "1," "2," "3," "4," If use cat(c, sep=",") I can't seem to assign it to an object, 1,2,3,4> myvec <- cat(c, sep=",") 1,2,3,4> myvec NULL and if I bypass the

Hello, I know of some various methods out there to utilize multiple processors but am not sure what the best solution would be. First some things to note: I'm running dependent simulations, so direct parallel coding is out (multicore, doSnow, etc). I'm on Windows, and don't know C. I don't plan on learning C or any of the *nix languages. My main concern deals with Multiple

What does missInfo compute and how is it computed? There is only 1 observation missing the ethnic3 variable. There is no other missing data. N=1409 > summary(MIcombine(mod1)) Multiple imputation results: with(rt.imp, glm(G1 ~ stdage + female + as.factor(ethnic3) + u, family = binomial())) MIcombine.default(mod1) results se (lower upper)

Hallo! I have a vector of ID's like so, id <- c(1,2,2,3,3,3,4,5,5) I would like to create a [start,stop] pair of vectors that index the first and last observation per ID. For the ID list above, it would look like 1 1 2 3 4 6 7 7 8 9 I haven't worked with indexes/data manipulation much in R, so any pointers would be helpful. Many thanks! ~~~~~~~~~~~~~~~~~~~ -Robin Jeffries Dr.P.H.

Is there an obvious reason why this won't loop to i=2 and beyond? There are many combinations of *st* & *vc* that don't exist in svc. For example, when s=1 there's only an entry at v=1. That's fine, the entry can stay 0. lookup.svc <- array(0,dim=c(length(unique(svc$st)),length(unique(svc$vc))), dimnames=list(unique(svc$st), unique(svc$vc))) for (i in

I want to set up a windows system task that will run a .R script at pre-specified times. Can someone please help with the command line syntax that I would assign to the task? I know that i can open a command prompt, type R, and then source the file, but I don't know how to pass multiple line arguments to the command line in a system task. Thanks, ~~~~~~~~~~~~~~~~~~~ -Robin Jeffries Dr.P.H.

Dear R users, I'm trying to extract from a given matrix (GROUP) the coordinates of the vertices of the different groups (i.e. 3, 7, 1 . . .) to plot the polygons to delineate the area in which each group "wins" and colour it diferentially. I can make a simple point plot, but I would like to add polygons with full colored area. The example is with a 5x5 matrix, but I'm working

I read somewhere (help list, documentation) that the random effects in lme4 uses sparse matrix "technology". I'd like to confirm with others that I can't use a sparse matrix as a fixed effect? I'm getting an "Invalid type (S4) " error. Thanks. ~~~~~~~~~~~~~~~~~~~ -Robin Jeffries Dr.P.H. Candidate in Biostatistics UCLA School of Public Health rjeffries@ucla.edu

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",

I know this is a simple question, but I have yet to master the apply statements. Any help would be appreciated. I have a column of probabilities and sample sizes, I would like to create a column of binomial random variables using those corresponding probabilities. Eg. mat = as.matrix(cbind(p=runif(10,0,1), n=rep(1:5))) p n [1,] 0.5093493 1 [2,] 0.4947375 2 [3,]

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

Hello, I need to plot the means of some outcome for two groups (control vs intervention) over time (discrete) on the same plot, for various subsets such as gender and grade level. What I have been doing is creating all possible subsets first, using the aggregate function to create the means over time, then plotting the means over time (as a simple line plot with both control & intervention

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:

I would like to run a logistic regression on some factor variables (main effects and eventually an interaction) that are very sparse. I have a moderately large dataset, ~100k observations with 1500 factor levels for one variable (x1) and 600 for another (X2), creating ~19000 levels for the interaction (X1:X2). I would like to take advantage of the sparseness in these factors to avoid using GLM.

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: >