similar to: apply on function with vector as result

Hi I would like to have something like str <- "df$JT == 12" fun <- function(df) { b <- eval(parse(str)) return(b) } but for performance "eval(parse(a))" should not be evaluated at each function call, but should work as fun <- function(df) { b <- df$JT == 12 return(b) } Do you have an idea how I can implement this? Thx Christof

Hi is there a automatic way that long distances between points are not connected. I have something like plot(x,y,type="o",...) atx <- seq(as.Date("2009-04-01"),as.Date("2011-04-01"),"month") axis.Date(1, at=atx,labels=format(atx, "%b\n%Y"), padj=0.5 ) but I do not want lines between points whose distance is greater than two weeks. thx

Hi how would you save conditions like a = "day > 100"; b = "val < 50"; c = "year == 2012" in a list? I like to have variables like "day", "val", "year" and a list of conditions list(a,b,c). Then I want to check if a & b & c is true or if a | b | c is true or similar things. Greetings Christof

Hi there are some predefined self-start functions, like SSmicmen, SSbiexp, SSasymp, SSasympOff, SSasympOrig, SSgompertz, SSflp, SSlogis, SSweibull, Quadratic, Qubic, SSexp (nlrwr) Btw, do you know graphic examples for this functions? The SSexpDecay (exponential decay) for y = (y0 - plateau)*exp(-k*x) + plateau from

Hi I like to use "axis.POSIXct" to plot days from 2006 till 2008. But I only have datas for the summer months. Is it possible to get two axis breaks, to have not so long distances without points? thx Christof

Hi xyplot(y ~ x | subject) plots a separate graph of y against x for each level of subject. But I would like to have an own function for each level. Something like xyplot(y ~ x | subject, panel = function(x,y) { panel.xyplot(x,y) panel.curve(x,y) { # something that dependents on the current subject ... } }) How I get the current

Hi one col in my Excel file contains many numbers. But on line 3000 and some other lines are strings like "FG 1". "RODBS" seems to omit this lines. "gdata" works, but is much slower. Is this a bug of RODBC or do I apply it wrong? Example with the same "file.xlsx" library(RODBC); excel <- odbcConnectExcel2007("file.xlsx") tab <-

Hi I would like to shorten mod1 <- nls(ColName2 ~ ColName1, data = table, ...) mod2 <- nls(ColName3 ~ ColName1, data = table, ...) mod3 <- nls(ColName4 ~ ColName1, data = table, ...) ... is there something like cols = c(ColName2,ColName3,ColName4,...) for i in ... mod[i-1] <- nls(ColName[i] ~ ColName1, data = table, ...) I am looking forward to help Christof

I've written a function, myFunc, that works fine with myFunc(data, ...), but when I use apply() to run it with an array of data apply(myArray, 1, myFunc, ...) I get a strange error: Error in match.fun(FUN) : '1' is not a function, character or symbol which really puzzles me because '1' is meant to be the margin of the array I want to apply over, but how come does apply()

Hi I want to add a row to a "data.table" in each round of a for loop. "rbind" seems to be a inefficient way to implement this. How would you do this? The "slow" solution: library(data.table) Rprof("test.out") dt <- data.table() for (i in (1:10000)) { # algorithm that generates a list with different values, # but same key-names, each round, for

Hello, everyone I have a piece of code that looks like this: mrets <- merge(mrets, BMM.SR=apply(mrets, 1, MyFunc, ret="BMM.AV120", stdev="BMM.SD120")) mrets <- merge(mrets, GM1.SR=apply(mrets, 1, MyFunc, ret="GM1.AV120", stdev="GM1.SD120")) mrets <- merge(mrets, IYC.SR=apply(mrets, 1, MyFunc, ret="IYC.AV120",

Hi, I want to fit nonlinear dose-response curves, as "fun(X,a,b,c)", for each of our 5 trail locations. Our data basis is something like location plot year dose response For each location there are 4 plots as repetitions (over 3 years). So the interactions "location*year" and "location*plot" should be random effects. There are some examples in "Mixed-Effects

Hi I have "observations" obs <- (11455, 11536, 11582, 11825, 11900, ...) and a simulation function f(A,B,C,D,E,F), so sim <- f(A,B,C,D,E,F) e.g. sim = c(11464, 11554, 11603, 11831, 11907, ...) now I would like to fit A,B,C,D,E,F such that "obs" and f(A,B,C,D,E,F) match as well as possible. A,..,F should be integers and have bounds. How would you solve this problem

Dear R-users Idea: Plot a dnorm line using specific mean/sd to complete a histogram (skewed). xs:range of y-values, ys: dnorm function Problem: I expected to multiply the ys function with the sample size (n=250-300). I was wondering about a factor between 12'000 and 30'000 to match the size of the dnorm line with the specific histogram. Thanks Sibylle hist(Biotree[Ld,]$Height2008,

Hello. I am new R user, so this question is probably quite stupid, but for the life of me I cannot figure out how to get predications using multivariate linear regression analysis. Single variable predictions work fine. I am trying the following: -- Known y's for known x's1 and x's2 ys <- c(133890, 135000, 135790, 137300, 138130, 139100, 139900, 141120, 141890, 143230, 144000,

Dear all, I'm having a problem with debugger() in both R 2.8.0 and R 2.12.0. Probably also versions in-between. I don't see it logged in the bug database, but it's hard for me to imagine that no-one else has encountered it. So my question is whether it's a known problem with a workaround, or do I log it as a new problem? The situation is that if I use

Here's some code to make lissajous dance. I've attached a small sample GIF. Cheers, Rob Steele robsteele at yahoo dot com plot.lissajous = function(omega.x, omega.y, delta = 0, num.thetas = 200) { thetas = seq(0, 2 * pi, length = num.thetas) xs = sin(omega.x * thetas + delta) ys = cos(omega.y * thetas) plot(xs, ys, type = 'l', lwd = 3, ann = FALSE, axes = FALSE) }

Can someone help me with this simple example? sq <- function() { y <- x^2 y } myfunc <- function() { x <- 10 sq() } myfunc() executing the above in R yields: > myfunc() Error in sq() : Object "x" not found I understand that R's scoping rules cause it to look for "x" in the environment in which "sq" was defined (the global environment in

David Brahm <brahm at alum.mit.edu> wrote: >VBMorozov at lbl.gov wrote: >> I would like to pass variables to a function in R in "by reference"... >Just in case the ensuing discussion got too esoteric, here's one simple answer: >R> x <- 1:10 >R> MyFunc <- function(x, zz) assign(deparse(substitute(zz)), sum(x), 1) >R> MyFunc(x,y) >R>

I may be doing this wrong! but I have a function which I have simplified a lot below. I want to pass some 'field names' of a data-frame to the function for it to then do some manipulation of. Here's my code: #build a simple dataset mydataset = data.frame (