similar to: ifelse help?

Hi All, I'm still pretty new to using R - and I was hoping I might be able to get some advice as to how to use 'apply' or a similar function instead of using nested for loops. Right now I have a script which uses nested for loops similar to this: i <- 1 for(a in Alpha) { for (b in Beta) { for (c in Gamma) { for (d in Delta) { for (e in Epsilon) { Output[i] <-

Dear r-help, I'm interested in finding a better way to add a column to a data frame when calculating the new column requires more than one conditional. For example, if I wanted to associate a character string in {"Pos","Neg","Zero"} with each number in the following data frame: > d <- data.frame(num = -2:2) > d num 1 -2 2 -1 3 0 4 1 5 2 I

All - I have a number of rows that I am assigning length classes to via l.class<-with(wae, ifelse((Length>=120)&(Length<130),"125", ifelse((Length>=130)&(Length<140),"135", ifelse((Length>=140)&(Length<150),"145", ifelse((Length>=150)&(Length<160),"155",

This is both a specific question and a general one. First, I am running 'fitdistr' from library(MASS) and I get the following: Error in fitdistr(templist, "weibull") : optimization failed What is the cause of the error? How can I tell? Can I just catch this error, report it and move to the next set of data (eat the exception)? Thank you. Kevin

I have a matrix of frequency counts from 0-160. x<-as.matrix(c(0,1,0,0,1,0,0,0,1,0,0,0,0,1)) I would like to apply a function creating a new column (x[,2])containing values equal to: a) log(x[m,1]) if x[m,1] > 0; and b) for all x[m,1]= 0, log(next x[m,1] > 0 / count of preceding zero values +1) for example, x[1,2] should equal log(x[2,1]/2) = log(1/2) = -0.6931472 whereas x[3,2] should

I am doing cluster analysis [hclust(Dist, method="average")] on data that potentially contains redundant objects. As expected, the inclusion of redundant objects affects the clustering result, i.e., the data a1, = a2, = a3, b, c, d, e1, = e2 is likely to cluster differently from the same data without the redundancy, i.e., a1, b, c, d, e1. This is apparent when the outcome is visualized

Dear R Group: I have little experience using R and even less experience with control flow type questions. See the following code: a1 = c(0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0) for(i in 1:1){ sx <- paste("a",i,sep="") s <- eval(parse(text = paste("a",i,sep=""))) {g = numeric(length(s)) k =

Hallo, I didn´t found any facilities for Halbergs cosinor analysis in R. This analysis is well known in the Chronobiology as the least square approximation of time series using cosine function of known period (in my case of 24hours-period). I tried to write a script but crashed... Can you give me some advices, please!? Thanks Anne Berger Institute of Zoo- and Wildlife Research, Berlin, Germany

Hi all, I can't come over a problem with formula. Suppose I have a coxmod model with the following formula: > somemod$formula Surv(lebzeit, tot == 1) ~ sex + (alter >= 65) + diff3k + zelltyp_k_c + q_nuc_3k + kar_k80_g80 + stadium and I want to drop the stadium explanatory variable from the model with > update(somemod, ". ~ . - stadium") I get the following messages:

Hi, How can I check if a certain ... argument has been passed on to my user-defined function or not? foo <- function(data, ...) { ### here I want to check whether xlab was passed with the ... arguments ### or if the ... arguments did not contain an xlab argument } I tried missing(xlab) , exists(xlab) and several other things but did not find a solution. TIA, Mark

Dear R-list members, Just wondering if there is any way to compute the duplication matrix in R. I tried to search for it but only found functions "xpnd" and "vech". Basically for a symmetric n by n matrix A, the duplication matrix D_n is a matrix of dimension n^2 by n(n+1)/2 such that D_n vech(A)= c(A), where c(A) just vectorizes A. The duplication matrix is defined on page

Dear All., I've created R-code for which a user will be asked to choose between 2 analyses. I've written one function for each type of analysis. Within each function, the users is prompted to enter information. An example is: cat("Enter value for lower Linf :\n") L1<-scan(n=1) cat("Enter value for upper Linf :\n") L2<-scan(n=1)

Dear R-helpers: I am new to R and ran into the following question and would appreicate your advice very much. My question: How to use a character vector that records object names as function input argument? I asked this question very recently and was advised to use get(). get() works when passing one single object name. but it does not work when passing multiple object names. For example, I

Dear R-helpers, I am very new to R and trying to run the conditional logit model using "clogit " command. I have more than 4000 observations in my dataset and try to predict the dependent variable from 14 independent variables. My command is as follows clmtest1 <- clogit(Pin~Income+Bus+Pop+Urbpro+Health+Student+Grad+NE+NW+NCC+SCC+CH+SE+MRD+strata(IDD),data=clmdata) However, it

Dear R users I would like to simulate underdispersed Poisson and binomial distributions somehow. I know you can do this for overdispersed counterparts - using rnbinom() for Poisson and rbetabinom() for binomial. Could anyone share functions to do this? Or please share some tips for modifying existing functions to achieve this. Thank you very much for your help and time Shinichi

I'm guessing there's a more efficient way to do the following using the index features of R. Appreciate any thoughts.... for (i in 1:nrow(dbs1)){ if(dbs1$Payor[i] %in% Payor.Group.Medicaid) dbs1$Payor.Group[i] = "Medicaid" if(dbs1$Payor[i] %in% Payor.Group.Medicare) dbs1$Payor.Group[i] = "Medicare" if(dbs1$Payor[i] %in% Payor.Group.Commercial)

I have consulted the intro and nabble but have not found an answer to what should be a simple question, here goes: I am doing a crosscheck of a data frame and pulling out a single value based on an inputted value ie based on x i will select y, or if x =2 then my code returns 7. x y 1 4 2 7 3 10 4 2 My code currently iterates through for as many times as the length of the x

Is there any similar function in R to the first. in SAS? What it dose is: Lets say we have this table: a b c 1 1 5 1 0 2 2 0 2 2 0 NA 2 9 2 3 1 3 and then I want do to do one thing the first time the number 1 appers in a and something else the secund time 1 appers in a and so on. so something similar to: if first.a { a$d<-1 }else{ a$d<-0 } This would give me

I am working with a dataset where there are 5 possible outcomes (coded 1:5), I would like to create 5 categorical variables (event1...event5). I am using a for loop an if statements, but I have a large dataset( approx 100,000 rows) it takes quite a bit of time, is there a way to speed this up? Here is some sample code of what I am currently doing. test2 <-rep(seq(1:5),2000) event1 <-

Hello list! I would like to fit a distribution to each of the peaks in a histogram, such as this: http://photos1.blogger.com/blogger/7029/2724/1600/DU145-Bax3-Bcl-xL.png . The peaks are identified using Petr Pikal peaks function ( http://finzi.psych.upenn.edu/R/Rhelp02a/archive/33097.html), but after that I am quite stuck. Any idea as to how I can: Fit a distribution to each peak Integrate the