similar to: Printing "pretty' vectors in Sweave

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

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

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.

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

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.

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 list, I have a vector of numbers, let's say: myvec <- c(2, 8, 24, 26, 51, 57, 58, 78, 219) My task is to reduce this vector to non-reducible numbers; small numbers can cross-out some of the larger ones, based on a function let's say called reduce() If I apply the function to the first element 2, my vector gets shorted to: > (myvec <- reduce(myvec[1])) [1] 2 24 51

I have been through the help file archives a number of times, and still cannot figure out what is wrong. I have a tab-delimited text file. 76Mb, so while it's large.. it's not -that- large. I'm running Win7 x64 w/4G RAM and R 2.10.1 When I open this data in Excel, i have 27 rows and 450932 rows, excluding the first row containing variable names. I am trying to get this into R as a

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

List, Consider the following data. gender mygroup id 1 F A 1 2 F B 2 3 F B 2 4 F B 2 5 F C 2 6 F C 2 7 F C 2 8 F D 2 9 F D 2 10 F D 2 11 F D 2 12 F D 2 13 F D 2 14 M A 3 15 M A 3 16 M A 3 17

Hi all, I’ve narrowed down a problem in my code to the following test case: - - - - typedef struct {float v[2];} vec2; typedef struct {float v[3];} vec3; vec2 getVec2(); vec3 getVec3() { vec2 myVec = getVec2(); vec3 res; res.v[0] = myVec.v[0]; res.v[1] = myVec.v[1]; res.v[2] = 1; return res; } - - - - Compiling this with any level of optimization for arm64 gives incorrect code,

Thanks Bruce. > On 4 May 2015, at 13:18, Bruce Hoult <bruce at hoult.org> wrote: > > I can confirm that, with Apple LLVM version 6.0 (clang-600.0.56) (based on LLVM 3.5svn) > > Very strange! Yes, that’s what I thought. I’ve also checked the binary downloads for OS X from llvm.org <http://llvm.org/> and get the same broken code from both the 3.5.2 and 3.6.0 releases.

Dear experts, I try not to trouble the list again after this question. I want to print this vector into a file > myvec [1] --Control --Control --Control --Control --Control HBA2 HBA1 [8] HBA1 --Control HBB --Control HBB HBA1 MBP [15] --Control HBA1 HBA2 HBB PTGDS GAPDH UBC [22] --Control GAPDH TPT1 HUWE1 PRM1 CKM

I'm having trouble getting ffdfindexget to work right in Windows. Even the most trivial of examples gives me problems. > myVec = ff(1:5) > another = ff(10:14) > littleFrame = ffdf(myVec, another) > posVec = ff(c(2, 4), vmode = 'integer') > ffdfindexget(littleFrame, posVec) Error in if (any(B < 1)) stop("B too small") : missing value where TRUE/FALSE

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.

Hi R-users, To automate the creation of scripts, I converted the code (example below) into a character string and wrote the object to a file: Repeat <- " myvec <- c(1:12) cat('vector= ', myvec, '\n') " write (Repeat, 'yourpath/test.R') the problem is that one line of the code is a "cat" command. In the output file (i.e. test.R), the newline

Dear list, This should be a simple one, I just cannot see it. I need to generate a sequence of the form: 4 5 6 13 14 15 22 23 24 That is: starting with 4, make a 3 numbers sequence, jump 6, then another 3 and so on. I can create a whole vector with: myvec <- rep(rep(c(F, T, F), rep(3, 3)), 3) Then see which are TRUE: which(myvec) [1] 4 5 6 13 14 15 22 23 24 I'd like to avoid