similar to: bootstrapping data.frame and matrix

This is one of those instances where a less superficial knowledge of R's technical details comes in really handy. What you need to do is convert the data frame to a single (numeric) vector for, e.g. a matrix() call. This can be easily done by noting that a data frame is also a list and using do.call(): ## imp is the data frame: do.call(c,imp) X11 X12 X13 X14 X15 X16 X17 X18 X19

Hello everyone, Thank you for this. Nonetheless it is not exactly want i need. I need mydata[[1]] to provide the values for all 3 variables (Y, X1 and X2) of the first imputation only. As it stands it returns the whole database. Any ideas? Best, ioanna ________________________________ From: Bert Gunter <bgunter.4567 at gmail.com> Sent: 24 May 2018 16:04 To: Ioanna Ioannou Cc:

Hello everyone, I want to transform a data.frame into an array (lets call it mydata), where: mydata[[1]] is the first imputed dataset...and for each mydata[[d]], the first p columns are covariates X, and the last one is the outcome Y. Lets assume a simple data.frame: Imputed = data.frame( X1 = c(1,2,1,2,1,2,1,2, 1,2,1,2,1,2,1,2), X2 =

Dear r-helpers, I'm looking for a way of sorting variable names in a "natural" order, when the names are composed of digits and other characters. I know that this is a vague idea, and that sorting character strings is a complex topic, but perhaps a couple of examples will clarify what I mean: > s <- c("x1b", "x1a", "x02b", "x02a",

http://biomet.oxfordjournals.org/cgi/reprint/86/3/677 biometrika1999 http://biomet.oxfordjournals.org/cgi/reprint/94/4/1006 biometrika2000 Hi All: I just want to try some luck. I am currenly working on my project,one part of my project is to reanalysis the kenward cattle data by using the method in Mohsen's paper,but I found I really can get the same or close output as he did,so,any

Hi, I'm a novice R user, much more used to SAS. My problem is pretty simple - basically, in a data frame, I have variables named x1,....,x10 and y1,...,y10; and I would like to create r1 = x1 / y1 etc Apologies if this is way too rudimentary - but I couldn't find any posts online which solve this exact issue. Cheers, Andre

R-Helpers; This seems simple to set graphic parameter, but I tried plot a graph with 10 intervals in x axis with par(xaxp = c(0, 150, 10) but to no avail: par(xaxp =c (0, 150, 10)) plot(age, y18, type="n", ylab="Height (m)", xlab=" age (Yrs)", font = 2) lines(age, y6, lty = 4, lwd = 2) lnes(age, y10, lty = 1, lwd =2) lines(age, y14, lty = 2, lwd =2)

Dear list, I have problem that I cannot solve and would like to ask your opinion. I tried to ask a few days ago already but got no answer and all my attempts to solve it by myself since then failed. Sorry for repeated posting! Here the problem broken down a bit. My problem basically is, that I want to use the elements of a character vector as names for objects and by recalling only the

Dear R developers, I noticed a bug in the stats4 package, specifically in the confint method applied to ?mle? objects. In particular, when some ?fixed? parameters define the log likelihood, these parameters are stored within the mle object but they are not used by the ?confint" method, which retrieves their value from the global environment (whenever they still exist). Sample code: >

Dear all I used R2WinBUGS package's bugs() function to generate MCMC results. Then I tried to save the simulation draws in R, using read.bugs() function. Here is a simple test: ###################### library(coda) library(R2WinBUGS) #fake some data to test beta0=1 beta1=1.5 beta2=-1 beta3=2 N=200 x1=rnorm(N, mean=0,sd=1) x2=rnorm(N, mean=0,sd=1) x3=rnorm(N, mean=0,sd=1) lambda2= exp(beta0+

Dear experts, I have in all 14 matrices which stands for gene expression divergence and 14 matrices which stands for gene sequence divergence. I have tried joining them by using the concatanation function giving SequenceDivergence <- c(X1,X2,X3,X4,X5,X6,X7,X8,X9,X10,X11,X12,X13,X14) ExpressionDivergence <- c(Y1,Y2,Y3,Y4,Y5,Y6,Y7,Y8,Y9,Y10,Y11,Y12,Y13,Y14) where X1,X2..X14 are the

Hi All, I am making a serious effort to try to learn R, but one hurdle I am facing is that I need to "see" the data as I walk through the examples in the packages. For instance, many examples on the web start by a command like data("wines"). How can I actually view what the dataset looks like prior to transformations and analysis? I have tried to use edit() , print, and

After searching in R- Introduction, FAQ, help... I don't understand this: I write a function in a file (.R): tt <- function(mc) { date() mc<-read.csv2("machines.txt",na.strings="") date() } I source it in R and I type tt(). The answer is > tt() [1] "Mon Aug 14 11:18:25 2000" > The instructions following the first "date()" are ignored. Why?

Can somebody help me with the following issue (SEM in R), please:   When I run the model (includes second order models) in R, it gives me the following:   1)       In sem.default(ram = ram, S = S, N = N, param.names = pars, var.names = vars,  :   Could not compute QR decomposition of Hessian. Optimization probably did not converge.   2)       I have aliased parameters and NaNS   or sometimes when

DeaR useRs: I would like to assign a values in an object using a loop 'for'. This is a reduce example of my problem, my real problem is a few complicated: for (j in 1:10) { x.j<-rnorm(100) } I want to create 10 objects as "x.1, x.2, ... , x.9, x.10" with values in it. I used the "assign" function but nothing happens. Thank you very much

Hello Community: I''m a brand new user of Ruby on Rails, and am having a great deal of trouble compiling from source. I''m using the tutorial at http://hivelogic.com/articles/2005/12/01/ruby_rails_lighttpd_mysql_tiger to complete the install. Readline and Ruby installed just fine, and the Ruby Gems appeared to. But when I tried to sudo gem install Rails --include-dependencies,

Dear all, I'm looking for primary help at aggregating table() results and at writing a loop (if useful) My dataset ( http://goo.gl/gEPKW ) is composed of 23k rows, each one representing a point in the space of which we know the land cover over 10 years (column y01 to y10). I need to analyse it with a temporal sliding window of 5 years (y01 to y05, y02 to y06 and so forth) For each period

Hello, I am using using dovecot 2.1.7 from debian stable: namespace inbox { inbox = yes location = mailbox Drafts { special_use = \Drafts } mailbox Junk { special_use = \Junk } mailbox Spam { special_use = \Junk } mailbox Sent { special_use = \Sent } mailbox "Sent Messages" { special_use = \Sent } mailbox Trash { special_use = \Trash

Many thanks to Peter Dalgaard BSA and Uwe Uwe Ligges for their prompt responses. It turns out xaxp can not be set by par(xaxp = c(x1, x2, n)) as indicatedd in Help for 'par' document. Both pointed me to the right direction by setting axes = F or xaxt = "n" in plot() and using axis(1, seq=c(0,150,15)) to produce an axis with desired intervals. Richard My original question:

Dear experts, I have in all 14 matrices which stands for gene expression divergence and 14 matrices which stands for gene sequence divergence. I have tried joining them by using the concatanation function giving SequenceDivergence <- c(X1,X2,X3,X4,X5,X6,X7,X8,X9,X10,X11,X12,X13,X14) ExpressionDivergence <- c(Y1,Y2,Y3,Y4,Y5,Y6,Y7,Y8,Y9,Y10,Y11,Y12,Y13,Y14) where X1,X2..X14 are the