similar to: dimnames in an array(I'll be grateful if this message will be passed to all list users)

Hello, I'm working with an array; I'm trying to make it so that an array of dim(42,2,2) has names whose length corresponds to that of the array, and am hoping someone with experience with this can see what I'm not doing correctly: data11 = array(0,c(41,2,2)) y = lsoda(x0,times,fhn$fn.ode,pars)#This is make.fhn() from colloc infer package# y = y[,2:3]

Suppose I have following dataset : > head(data1) Date Return 1 03/31/00 0.14230650 2 04/28/00 -0.03276228 3 05/31/00 -0.06527890 4 06/30/00 -0.04999873 5 07/31/00 -0.01447902 6 08/31/00 0.22265729 Now I convert it to zoo object : > data11 = zoo(data1[,2], as.Date(data1[,1], format="%m/%d/%y")) > head(data11) 2000-03-31 2000-04-28 2000-05-31

NOTE: posted this to gluster-devel when I meant to post it to gluster-users 01 | 02 mirrored --| 03 | 04 mirrored --| distributed 05 | 06 mirrored --| 1) Would this command work for that? glusterfs-volgen --name repstore1 --raid 1 clustr-01:/mnt/data01 clustr-02:/mnt/data01 --raid 1 clustr-03:/mnt/data01 clustr-04:/mnt/data01 --raid 1 clustr-05:/mnt/data01 clustr-06:/mnt/data01 So the

Hi, I got following error in write.table() : > write.table(dataa, file="c:/data1.csv", row.names=F, col.names=T, sep=",") Error in file(file, ifelse(append, "a", "w")) : cannot open the connection In addition: Warning message: In file(file, ifelse(append, "a", "w")) : cannot open file 'c:/data1.csv': Permission denied

Hello, I am using Dr. Harrell's rms package to make a nomogram. I was able to make a beautiful one. However, I want to change 5-year survival probability to 5-year failure probability. I couldn?t get hazard rate from Hazard(f1) because I used cph for the model. Here is my code: library(rms) f1 <- cph(Surv(retime,dfs) ~ age+her2+t_stage+n_stage+er+grade+cytcyt+Cyt_PCDK2 , data=data11,

Hello, I would like to read sets of files within a folder, perhaps using recursive methods. Right now, I rename the files before import. It would be even better to do this without renaming files, without providing explicit filenames, perhaps by importing files based on chronology, and translating each filename into a header? Please excuse my ignorance, and help cure my clunky programming

The code given below worked well. However, the problem is that when I typed dir1 to see the results I found that R order the files as: [1] "data1.flt" "data10.flt" "data100.flt" "data101.flt" [5] "data102.flt" "data103.flt" "data104.flt" "data105.flt" [9] "data106.flt" "data107.flt"

Does anyone know the algorithm that Asterisk uses to figure out when you'll be speaking with an agent? I've heard it say such bizarre things as '2 minutes' when there area 2 calls waiting ahead of a person and 1 agent logged in.

Hi, With the following Sweave minimal file: ---<--------------------cut here---------------start------------------->--- \documentclass{article} \usepackage{Sweave} \begin{document} <<binom-sim>>= thetas <- seq(0, 1, by=0.001) prior <- rep(1, length(thetas)) / length(thetas) lik <- dbinom(1, 1, thetas) lik.p <- prior * lik post <- lik.p / sum(lik.p)

Dear people, I'm trying to do some analysis of a data using the models by Royle & Donazio in their fantastic book, particular the following function: http://www.mbr-pwrc.usgs.gov/pubanalysis/roylebook/panel4pt1.fn that applied to my data and in the console is as follows: > `desman.y` <- structure(c(3L,4L,3L,2L,1L), .Names = c("1", "2", "3",

Hi the list, I would need some advice on something that looks like a FAQ: the possibility of providing vectors to optim() function. Here is a stupid and short example summarizing the problem: -------------------------------- example 1 ------------ 8< ---------------------- library(stats4) data <- rnorm(100,0,1) lik1 <- function(m, v, data) { N <- length(data) lik.mean <-

--- On Mon, 3/12/12, aleksandr shfets <a_shfets at mail.ru> wrote: > From: aleksandr shfets <a_shfets at mail.ru> > Subject: Fwd: Re[2]: [R] B-spline/smooth.basis derivative matrices > To: "Vassily Shvets" <shv736 at yahoo.com> > Received: Monday, March 12, 2012, 5:15 PM > > > > -------- ???????????? ????????? > -------- > ?? ????:

I am looking for some help at removing low-frequency components from a signal, through Moving Average on a sliding window. I understand thiis is a smoothing procedure that I never done in my life before .. sigh. I searched R archives and found "rollmean", "MovingAverages {TTR}", "SymmetricMA". None of the above mantioned functions seems to accept the smoothing

I am sorry if this question is vague or uninformed. I am just learning R and struggling. I am using the book Hierarchical Modeling and Inference in Ecology and they provide examples of R code. I have the following code from the book but when I run it I don't get any output. I cannot get the values of 'out' to show up. Basically, I just want to see my estimates for b0,

I'd like to have a class A that computes a likelihood, and a subclass B that computes the same likelihood by sometimes throws in an additional term (B includes measurement error). So B's likelihood needs to call A's, and then (sometimes) multiply by an additional term. It sounds as if, in the S3 scheme, NextMethod is supposed to do this: like.A <- function(stuff) compute value

Hello, I am trying to bootstrap a function that extracts the log-likelihood value and the nls coefficients from an nls object. I want to sample my dataset (pdd) with replacement and for each sampled dataset, I want to run nls and output the nls coefficients and the log-likelihood value. Code: x<-c(1,2,3,4,5,6,7,8,9,10) y<-c(10,11,12,15,19,23,26,28,28,30) pdd<-data.frame(x,y)

Hi, My name is Laura. I'm a PhD student at Queen's University Belfast and have just started learning R. I was wondering if somebody could help me to see where I am going wrong in my code for estimating the parameters [mu1, mu2, lambda1] of a 2-phase Coxian Distribution. cox2.lik<-function(theta, y){ mu1<-theta[1] mu2<-theta[2] lambda1<-theta[3]

hi folks, I'm trying to build a table that contains information about a series of General Linear Models in order to calculate Akaike weights and other measures to compare all models in the series. i have an issue with indexing models and extracting the information (loglikehood, AIC's, etc.) that I need to compile them into the table. Below is some sample code that illustrates my

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Dear R users, When I run the code below, I get the error "Error in integrate(integrand, 0, Inf) : non-finite function value". The code works if the function returns only "sum(integ)". However, I want to add "cmh" to it. When I add "cmh" I get that error. I can't figure out why this is happening because my integrate function has nothing to do with