similar to: dropping variables from a data frame inside a function

Hey everybody, I am looking for a way to loop commands over several variables in a dataframe. Basically I want to do something like this: ti1<-aggregate(dataframename$y1, by=data.frame(dataframename$aggregationvar), sum,na.rm=TRUE) This works fine as it is but i want to do it for several variables thereby generating several tix. I tried with a for-loop but the

I am trying to understand the concept of lexical scope in "An Introduction to R" by the R Core development team. I'd appreciate it if someone would explain why the following example does not work: q <- function(y) {x + y}; w <- function(x){q(x)}; w(2); According to the discussion of Scope on page 46, it seems to me that R will interpret the free variable x in q as the

I am attempting to add a calculated column to a data frame. Basically, adding a column called "newcol2" which are the stock closing prices from 1 day to the next. The one little hang up is the name of the column. There seems to be an additional data column name included in the attributes (dimnames?). So when i run HEAD(DATAFRAMENAME) i get the column name = "Open". but

I just installed R 2.12.1, and when I went to run a few old programs with it, nothing worked. I got a ton of error messages saying such and such package was built before R 2.10.0 and needed to be reinstalled. These were not just warning messages, but error messages that prevent the programs from running when they were running just fine with R 2.10.1 For some of those packages, such as deSolve, I

Dear R users, I have a simple question on variable manipulation. Imagine I have an object "OBJ" that has "toto" as one of its variables. I would like to understand why if I do > varname <- "toto" >OBJ$varname returns no results whereas > OBJ[varname] returns the column entitled

I could use some help understanding how nls parses the formula argument to a model.frame and estimates the model. I am trying to utilize the functionality of the nls formula argument to modify garchFit() to handle other variables in the mean equation besides just an arma(u,v) specification. My nonlinear model is y<-nls(t~a*sin(w*2*pi/365*id+p)+b*id+int,data=t1,

Dear all, I have two probably very easy questions: (1) Is there a way to access certain variables by their string-based name representation? Example: numbers <- c("one", "two", "three") varname <- "numbers" print(varname[2]) (2) I need this functionality for a customized na.exclude() function that I am building, which should only exclude rows

Hi all. I'm looking for robust ways of building lagged variables in a dataset with multiple individuals. Consider a dataset with variables like the following: ## set.seed(123) d <- data.frame(id = rep(1:2, each=3), time=rep(1:3, 2), value=rnorm(6)) ## >d id time value 1 1 1 -0.56047565 2 1 2 -0.23017749 3 1 3 1.55870831 4 2 1 0.07050839 5 2 2 0.12928774 6

The following command, issued from the DOS command prompt (running Windows XP), produces the intended result of a .csv file created by program.R: ?c:\program files\R\R-2.8.0\bin\Rterm.exe? --save < "c:\TEMP\program.R" However, when I create a file called Rbatch.bat that contains exactly the line above, and try to execute it (by double clicking or via the Shell command in an Excel

Does anyone know if any R package has a function that will conduct Hollander's test of bivariate symmetry? (Hollander, Biometrika, 1971) Either the exact test or an asymptotic version would be sufficient for my purposes. Thanks. Joe Boyer Statistical Sciences Renaissance Bldg 510, 3233-D Mail Stop RN0320 8-275-3661 cell: (610) 209-8531 [[alternative HTML version deleted]]

Hi Folks, I'm wondering if there's a secret trick to achieve the following. I have some big code for analysis related to a named variable, which will be one of several in the columns of a dataframe, and I would like to be able to choose between a run for just one of these variables, or a run which loops over them all. So, for a single run, I could have the following kind of thing in a

Is there a package in R that can do a variability plot? A variability plot is a kind of categorized dot plot. (If there is a lot of data in each category, box plots are used rather than dot plots.) Usually, the categories are factor level combinations. All the dot plots appear in the same window; below the x-axis a hierarchy of factors shows which dot plot corresponds to which factor-level

I'm trying to understand the use of recursive functions described on page 45 of An Introduction to R by the R core development team. A function is a list of expressions, which all get executed with only the last being assigned to a global variable, right? So if a function refers recursively to itself, it should simply start with the first expression and go from there. At least that is my

The first program generates an error message and does not execute the regression of y on x. x<-1:10; y<-rnorm(10) + x; prac <- function( model, wghts ){ lm(model, weights = wghts) } prac(model = y~x, wghts = rep(1, 10)) But the next program works: x<-1:10; y<-rnorm(10) + x; prac <- function( y, x, wghts ){ lm(y~x,

Greetings guRus -- If a variable, e.g., 'varname', is a character string, e.g. varname <- "datavector", and I want to apply a function, such as table(), to datavector, what syntax or method will do so using only the variable varname? This seems similar to indirect addressing, but I have not seen a method for it in the R manuals. Is there a general name for such indirect

Hi, I would like to store some text and decimal values in the following form: name dec.val dec.val ... dec.val name dec.val dec.val ... dec.val ... name dec. val dec.val ... dec.val To do so, I created a matrix of the necessary size (x row per y cols) with the command matrixname <- matrix(0,x,y) and proceeded to fill in the matrix with information drawn from a data frame. The

I keep finding myself in a situation where I want to calculate a variable name and then use it on the left hand side of an assignment. For example iteration <- 1 varName <- paste("run",iteration,sep="") myList$parse(text=varName) <- aColumn I want to take some existing variable "aColumn" and use the name "varName" name for it and put it into a

getenv(<varname>) currently returns "" if the <varname> is undefined. However, if <varname> is defined but empty, getenv(<varname>) still only returns "". I think this is quite unfortunate but consistent with the prototype. --- I'd propose to change the current behavior. Something which should be pretty back compatible would for the first

Dear R community, I have one function, it works for small data set, but does not work on large data set, can anyone help me with this? > #creat new variable by dividing each aa dimer by total_length. > imper<-function(x, file) { + round(x/file$length, 5) + } > dim(test) [1] 999 2402 > test[varname[2:2401]]<-

Dear all I am looking for a shorter way and more elegant to write the following for (i in c(1:length(Shadowlist))){ filename<-paste('/home/apa/maps/',model,i,'.mat',sep="") varname<-paste(model,'_shadow',i,sep="") eval(parse(text=paste('writeMat(filename,',varname,'=Shadowlist[[i]])',sep=""))) } actually I do not