similar to: recode based on filter

Dear list, I've recently came across a problem that I think I've solved and that I wanted to share with you for two reasons: - Maybe others come across the same problem. - Maybe someone has a much simpler solution that wants to share with me ;-) The problem is as follows: expand.grid() allows you to generate a data.frame with all combinations of a set of values, e.g.: >

Hi, I wonder how to pass several functions and their arguments as arguments to a function. For example, the main function is f = function(X ) { process1(X) ... process2(X) } I have a few functions that operate on X, e.g. g1(X, par1), g2(X, par2), g3(X, par3). par1, par2 and par3 are parameters and of different types. I would like to pass g1, g2, g3 and their arguments to f and g1,

Hello, unfortunately, I don't know a better subject. I would like to be very flexible in how to process my data. Assume the following dataset: par1 <- seq(0,1,length.out = 100) par2 <- seq(1,100) fac1 <- factor(rep(c("group1", "group2"), each = 50)) fac2 <- factor(rep(c("group3", "group4", "group5", "group6"), each =

Hi, I cannot figure out how to draw a certain plot: could someone help me out? I have this data.frame from a survey my.data that looks like something like this: col1 col2 col3 col4 1 5 5 4 5 2 3 5 3 1 3 2 3 4 5 4 3 1 1 2 5 5 5 4 5 6 4 2 5 5 .... Each row represents a single questionnaire

Hi R users: I'm trying to make a function where two of the parameters are functions, but I don't know how to put each set of parameters for each function. What am I missing? I try this code: f2<-function(n=2,nsim=100,fun1=rnorm,par1=list(),fun2=rnorm,par2=list()){ force(fun1) force(fun2) force(n) p1<-unlist(par1) p2<-unlist(par2) force(p1) force(p2)

Dear R users: I have a problem about catch the value from function. I have following two functions (part): sbolus1 <- function() { ....... for( i in 1:Subject) { kel<-par1 Vd<-par2 PKindex<-sbolus1.out(PKtime,kel,Vd,defun,par1,par2,Dose,i) } savefile(PKindex) } sbolus1.out<-function(PKtime,kel,Vd,defun,par1,par2,Dose,i) { time<-PKtime$time

After a few days of work, I think I nearly have it. Unfortunately, theta is unchanged after I run this (as a script from a file). I thought that theta would contain the fitted parameters. The goal here is to find the least squares fit according to the function defined as "rss" subject to the constraints defined as ui and ci. I defined ui and ci to (hopefully) force par2 and par3

Hi R-devel, I am facing a situation where the number of options I would like to propose to the user is somewhat big (and could easily increase more and more as I will code up a little more - even coming to a point where an user should be able to implement his own options). What we have to handle options is the couple: options(par=value) and getOption("par") I was aking myselft what

I have a data.frame with ~100 columns and I need a barplot for each column produced and saved in some directory. I am not sure it is possible - so please help me. this is my loop that does not work... vars <- list (substitute (G01_01), substitute (G01_02), substitute (G01_03), substitute (G01_04)) results <- data.frame ('Variable Name'=rep (NA, length (vars)),

Hi there again, I have a problem with the "parse"-command. First of all, I show you in a simplified way, what I am trying to do and what "R" answers: > test [1] "u.g$par1, u.g$par2" > mode(test) [1] "character" > ausdruck <- parse(text = test) Error in parse(file, n, text, prompt) : syntax error in "u.g$par1,"

Hi, I wonder how to pass several functions and their arguments as arguments to a function. For example, the main function is f = function(X ) { process(X) ... process(X) } I have a few functions that operate on X, e.g. g1(X, par1), g2(X, par2), g3(X, par3). par1, par2 and par3 are parameters and of different types.

Hi, I am currently working with the sem package in R, to create pathway diagrams. Id like to use the standardized path coeffcients. To get these, I use std.coef. However, using this yields only the standardized coefficients, but does not give me the standard error. Does someone know how to get std.coef to show the standard error of the standardized path coefficients as well? Thanks, Bastiaan

Dear all, Using: library(vegan) data(BCI) mod <- radfit(BCI[1,]) mod RAD models, family poisson No. of species 93, total abundance 448 par1 par2 par3 Deviance AIC BIC Null 39.5261 315.4362 315.4362 Preemption 0.042797 21.8939 299.8041 302.3367 Lognormal 1.0687 1.0186 25.1528 305.0629 310.1281

Hi all, I'm trying to use lapply on a list with the following command: out<-lapply(mylist,myfun,par1=p,par2=d) (1) where myfun<-function(x,par1,par1) {.....} (2) now this function is in fact a wrapper for some Fortran code I have written so I think this might be the problem. When I call lapply() as in (1) I get the following message: Error in get(x,

Dear R useRs, I have a problem with nls.lm function of minpackl.lm package. I need to fit the Van Genuchten Model to a set of data of Theta and hydraulic conductivity with nls.lm function of minpack.lm package. For the first fit, the parameter estimates keep changing even after 1000 iterations (Th) and I have a following error message for fit of hydraulic conductivity (k); Reason for

Hi, I would like some help regarding the LSR pass. It seems that it likes to duplicate address calculations as in the case above, which is highly undesirable on my target. I wonder if there is any way to tell LSR to not duplicate the code in cases like this? Or could I perhaps run CSE after LSR again? What is the logic behind this transformation? It seems that a LSR pass should not insert a

width <- 7 height <- 5 # create whatever device type # and have cex=1 before setting par(mai=) windows(width=width, height=height, rescale="R") oldmai <- par("mai") par(cex=1) par(mai=oldmai) plot.new() par(usr=c(0,2,0,2)) par(cex=2) par1 <- par() text(1,1,"there is hardly anything i know for sure\nneither of the future nor of the past\nnor should i know what

Dear R-list, I'm working with a data frame which dimensions are > dim(GERU) [1] 3468 318 and looks like > GERU[1:10,1:10] ped ind par1 par2 sex sta rs7696470 rs7696470.1 rs1032896 rs1032896.1 1 USA5854 2 0 0 2 1 4 4 1 1 2 USA5854 3 1 2 1 1 4 4 1 1 3 USA5854 4 1 2 2 2

Hello, I am trying to analyze sociological survey data using R. It is often important in survey to calculate both the actual factor sums and percentages (easily done with describe() ), but also the numbers and total percentage of NA's. Often it is important to present NA's in graphs besides the factors. Is there any easy way to make R treat NA's as if those were factors besides other

Hi, I have downloaded a R script from http://www.wessa.net/rwasp_edauni.wasp#output. This script produces a densityplot graphic, amongst others, when is executed from the web page. However, when I run it in my machine the *densityplot* function produces any output, I mean a blank graphic. But, it's interesting if I run the following lines in the R interactive console: > y <-