similar to: Lots of huge matrices, for-loops, speed

Dear R-experts! I am currently running a meta-analysis with the help of the great metafor package. However I have some difficulties setting up my raw data to enter it to the meta-analysis models. I have a group of subjects that have been measured in two continuous variables (A & B). I have the information about the mean of the two variables, the group size (n) and the standard deviations of

Hi, If I create a formula with say 100 terms and then paste it: xnam <- paste("x", 1:100, sep="") fmla <- as.formula(paste("y ~ ", paste(xnam, collapse= "+"))) paste(fmla) The result seems to cut off everything after the first 500 characters and gives no warning message. I have the most recent version of R from the R website and the problem occurs

Hi, Can you please help me with this please? What I am trying to do is call a vector from R function and used in the new function So I create 4 functions with these arguments M11 <- function(TrainData,TestData,mdat,nsam) { ls <- list() I have few statments one of them is vectx <- c(,1,2,3,4,5,6,6) vectz <- c(12,34,5,6,78,9,90) and then................ ls(vectx=vtecx,vectz=vectz)

hi netters i have a vector NAMES containing a series of variable names: NAMES=c(x,r,z,m,st,qr,.....nn). i wanna fit a regression tree by using the code: my.tree<-tree(y~x+r+z+m+....nn,my.dataframe) but i don't want to type out "x+r+z+m+....+nn" one by one, as there are so many variables. besides, sometimes i wanna put the code in a function. so i need to have the

Hi, I'd like to apply a 2^k factorial design with k=10 parameters. Obviously this results in a quite long term for the model equation due to the high number of combinations of parameters. How can I specify the equation for the linear model (lm) without writing all combinations explicitly down by hand? Does a R command exist for this problematic? Thanks for your help in advance, Sven

Hi! I had a database with some variables in sequence. Let me say: TX01, TX02, TX03 and TX04. But I need to run some regressions changing the variables... so: variable <- paste("TX0", 1:4, sep="") for(i in 1:4){ test[i] <- lm(variable[i] ~ INCOME, data=database) } But doesn't work... lm tries to find a variable inside database named variable[i] ... Suggestions?

Dear all, I am working on a function formula.design that should automatically generate reasonable lm formulae for a number of different designs. All works well as long as all variables used are columns of the design data frame. For one function, I would like to incorporate a dummy variable for center points that is not a column of the design. Without this function, it would work like this (at

Hello! First, I must also congratulate the R core team with their accomplishment! I have gotten to like R a lot, and I have recommended it for inclusion in an "Astronomy for Linux"-distribution which is in use by many professional astronomers and observatories. I'm currently working on importing data from files created by a C program (that I have not written myself, I have the

Hi, I have several Debian servers with puppet 0.23.2. Part of my manifest looks like this: class virt_all_users { @group { "andy": ensure => "present", gid => "1000" } @user { "andy": ensure => "present", uid => "1000",

Hi everyone - I'm trying to do a forward stepwise regression (I've tried both step and stepAIC) inside of a function. I can do it outside the function with no problems (first example in code below). I can also do a backward stepwise regression inside a function (second example), but forward stepwise regression ( third example ) fails with the error: "Error in

Hi, I am fitting a weighted least square regression and trying to compute SSE,SST and SSReg but I am not getting SST = SSReg + SSE and I dont know what I am coding wrong. Can you help please? xnam <-colnames(X) # colnames Design Matrix fmla1 <- as.formula(paste("Y ~",paste(xnam, collapse=

So 4.18.10 has this fix of the bug as observed in that respect, but I think you are seeing a broader example of that issue. NFS4 in this context is not actual NFS, but a type of unix filesystem permission system closely modelled on NT ACLs, deployed in many filesystems Samba uses, as the translation is much more direct. But even without that, it may be we are seeing the same issues, say for

Hi, I am trying to write a loop to recode my data from -999 to NA in R. What's the most efficient way to do this? Below is what I'm presently doing, which is inefficient. Thanks, Chris dat0 <- read.table("time1.dat") colnames(dat0) <- c("e1dq", "e1arcp", "e1dev", "s1prcp", "s1nrcp", "s1ints",

Well, that's a convincing argument, but maybe it's the name that's worrying some of us. Maybe it would be more intuitive if called set.na (sorry, I mean setNA). Also "is.na<-" cannot be used to create a new variable of NAs, so is not a universal method, which is a shame for its advocates. I note also that for a vector you can assign a new NA using either TRUE or

Dear all, I have just uploaded to CRAN the version 1.6 of the package 'adehabitat'. Significant changes are listed below: * The package has been reorganized into four parts (see ?adehabitat-package for a description): (i) management of raster maps, (ii) habitat selection / ecological niche analysis, (iii) home range analysis, and (iv) analysis of animals trajects. The package contains

Dear all, I have just uploaded to CRAN the version 1.6 of the package 'adehabitat'. Significant changes are listed below: * The package has been reorganized into four parts (see ?adehabitat-package for a description): (i) management of raster maps, (ii) habitat selection / ecological niche analysis, (iii) home range analysis, and (iv) analysis of animals trajects. The package contains

Dear developers, currently (rev 59060), plot.table and Axis.table do not forward their '...' argument to their calls to axis(). Thus, some graphical parameters (such as col.axis, cex.axis, font.axis) in '...' are ignored (for plot.table: partially ignored [for the x-axis]), which seems to be a minor bug. As a minimal reproducible example, see e.g.: