similar to: dynamic argument names and values as variables inside a loop

Hello R-Users, I would like to use an iterative loop to collect user input from within a function. I'm sure that this would be some combination of "for","break", and "next" but have not been able to get the syntax down. I would like to print some text to the screen at each step in the loop, ask the user for input which is saved in an object, and then advance the

Hello All, I've been using R for two years now and I am happy to say this is the first time I could not find the answer to my problem in the R-help archives. Here is the pending problem: I want to be able to insert delimiters, say commas, into a string of characters at uneven intervals such that: foo<-c("haveaniceday")#my string of character bar<-c(4,1,4,3) # my vector of

Hello All, I have had considerable bad luck with attempting the following with for loops. Here is the problem: # Suppose we have a data.frame with the following data, which can be considered a type of edgelist (for those with networks backgrounds): # # V1 V2 # 1 A # 1 A # 1 B # 2 A # 3 C # 3 A # 3 C # 3 B # # I want the output of the function to produce a matrix, such that #each factor of

Hi, The result of as,character() on 'srcref' objects doesn't have the closing ')' in some cases involving 'quote': > e4 <- quote({2+2}) > class(attr(e4, "wholeSrcref")) [1] "srcref" > as.character(attr(e4, "wholeSrcref")) [1] "e4 <- quote({2+2}" As a result printing the object also lacks it and gives an

wholeSrcref attribute is documented in ?parse to be the source reference corresponding to the already parsed text. The implementation in the parser matches the documentation - the code stops at the last byte/character of the expression, that is, on the closing brace - which is the "already parsed text". I think this works as documented (also source() uses the current implementation

Hello,   I'd like to generate automatically all the possible combinations of a set of 8 variables (there are 535, too many to do it by hand). For example:   input: varA, varB, varC output: varA+varB+varC             varA+varB             varA+varC             varB+varC             varA             varB             varC Is there any function that produces this option?   Thank you [[alternative

Hi: Can anyone advice me on how to loop and perform a calculation through all the columns. here's my data xd<- c(2.2024,2.4216,1.4672,1.4817,1.4957,1.4431,1.5676) pd<- c(0.017046,0.018504,0.012157,0.012253,0.012348,0.011997,0.012825) td<- c(160524,163565,143973,111956,89677,95269,81558) mydf<-data.frame(xd,pd,td) trans<-t(mydf) trans I have these values that I need to

Hello, I have some code that currently works fine and I am endeavoring to convert the major pieces of it into functions. This involves taking "hard coded" names of variables that are used in various places and figuring out how to abstract them out into functions where the arguments (i.e. a list of variables)?can be passed to the parent function and used within that function for various

Dear R Users, Am using lm() with contrasts as below. If I skip the contrasts() statement, I get the coefficient names to be > names(results$coef) [1] "(Intercept)" "VarAcat" "VarArat" "VarB" which are much more meaningful than ones based on integers. Can anyone tell me how to get R to keep the coefficient names based on the factor levels

Hello, I have a dataframe of say 20 lines with one line per individual. I want to group these 20 individuals by length class (eg. of 5cm) and get the mean value of all the other variables (eg VarA and VarB) for each length class My dataframe is as follow: Length <- 10:30 VarA <- seq(1000,1200,10) VarB <- seq(500,700,10) Data <- cbind(Length,VarA,VarB) And I want to get something

Dear list members, Where can I find code for computing the p*p variance-covariance matrix given a vector of p variances (ordered varA, varB, ..., varp) and a vector of all possible correlations (ordered corAB, corAC, ..., corp-1,p)? I know that the covariance between 2 variables is equal to the product of their correlation and their standard deviations: corAB * varA^.5 * varB^.5 and so:

Dear R developers! Considering I got no response or comments in the general r-help forum so far, perhaps my question is actually better suited for this list? I have added some more hopefully relevant technical details to my original post (edited below). Any comments gratefully received! Best regards, David Kreil. ---------- Dear R experts, I have a problem that is a related to the question

Dear R-Core Team, I found an unexpected behaviour in utils::removeSource (also present in r-devel as of today). --- # create a function which accepts NULL argument foo <- function(x, y) { if (is.null(y)) y <- "default foo" attr(x, "foo") <- y x } # create a function which utilizes 'foo' testSrc <- function() { x <- 1:3 x <- foo(x,

Hi, I have a question about how I should report the results for a linear mixed effects model where the model includes as predictors three factors (facA, facB and facC), one of which (facA) interacts with the other two. facA and facB have two levels and facC has 3 levels. There are also several other continuous predictors (e.g. varA, varB, varC). My mixed model is specified with the following

Dear R-list, I have a data set (in the following example called "a") which have: one "subject indicator" variable (called "id") three dependent variables (varD, varE, var F) three independent variables (varA, varB, varC) I want to fit 9 lme models, one per posible combination (DA, DB, DC, EA, EB, EC, FA, FB, FC). In stead of writting the 9 lme models, I want to

Hi, I would like to extract the fitted values from a model using LMER but only for the fix portion of the model and not for the fix and random portion (e.g it is the procedure outpm or outp in SAS). I am aware of the procedure fitted() but I not sure it give the fitted values both for the fixed and random or only the fixed. I looked in the r help and the r list and I haven?t not found much

Hi, Suppose I have x = parse(text = " {y=50+50+50#'asfasf' } ") now x is an expression with some src attributes. > x expression({y=50+50+50#'asfasf' }) attr(,"srcfile") <text> attr(,"wholeSrcref") {y=50+50+50#'asfasf' } My question is, how can I get my string back (the string passed to parse() as the text argument)? >

Hi, I'm in the process of setting up a backup server for a somewhat antiquated NT4 server. Backup server is CentOS-4 (~ RHEL-4), kernel-2.6.9-11.EL, samba-client-3.0.10-1.4E, rsync-2.6.3-1, LANG=en_US.UTF-8. NT4 shares are mounted on the server and rsynced to local disk. This setup is working pretty well, however on the NT box there are some files with names containing odd characters like

Dear R users, I'm having a hard time with some very simple things. I have a time series where the dates are in the format 7-Oct-04. I imported the file with read.csv so the date column is a factor. The series is rather long and I want to plot it piece by piece. The function below works fine, except that the labels for date are meaningless (ie 9.47e+08 or 1098000000 - apparently the number of

Hi, Agreed that it would be better if sys.call() were to return "x" instead of "*tmp*", as it behaves as a local variable. Although I'm not sure what problem it would solve, the effect here is comparable to what happens when calling a function indirectly (although then you could use sys.call(2), which here doesn't work). But your other suggestion, accepting