similar to: nesting environments

Hi there, I was wondering whether there are flexible packages available with which you can create user interfaces? (I've read about "gWidgets"!?) For example in Matlab you can even create stand alone applications. Is it also possible for R in the same extend? Of course it should be platform independent if possible... And then I would like to know from people who know R as well

Hi there, I would like to design a graphical user interface to provide the functionality of my R-scripts to other users (not knowing anything about R...) Can anybody give me some hints which possibilities I have (advantages / disadvantages)? What do you use to build applications? Ciao, Antje

Hello, I tried to fit a poisson distribution but looking at the function fitdistr() it does not optimize lambda but simply estimates the mean of the data and returns it as lambda. I'm a bit confused because I was expecting an optimization of this parameter to gain a good fit... If I would use mle() of stats4 package or mle2() of bbmle package, I would have to write the function by myself

Hi there, I though there has been a possibility to force the output on the console with one element per line. Instead of this: > 1:10 [1] 1 2 3 4 5 6 7 8 9 10 something like this > 1:10 [1] 1 [2] 2 [3] 3 [4] 4 [5] 5 [6] 6 [7] 7 [8] 8 [9] 9 [10] 10 Can anybody help? Antje

Hello, I hope this question is not too stupid. I would like to know how to update levels after subsetting data from a data.frame. df <- data.frame(factor(c("a","a","c","b","b")), c(4,5,6,7,8), c(9,1,2,3,4)) names(df) <- c("X1","X2","X3") my.sub <- subset(df, X1 == "a" | X1 == "b")

Hello, I was wondering if I can plot two curves I get from "density(data)" into one plot. I want to compare both. With the following commad, I just get one curve plotted: plot( density(mydata) ) Sorry for this stupid question but I could not find a solution until now... Antje

Hello, I'm looking for a solution for the following problem: I have two vectors V1 <- c("apple","honey","milk","bread","butter") V2 <- c("bread","milk") now, I would like to know for each element in V1 if it's equal to one of the elements in V2 I could do: which(V1 == V2[1] | V1 == V2[2]) but what if I

Hi folks, I've just discovered that the following code leads to boxplot (surprisingly to me). Can anybody explain to me why? Is this documented somewhere? I've never consider this option before. x <- rnorm(300) l <- c(rep("label1",100), rep("label2",50), rep("label3",150)) df <- data.frame(as.factor(l), x) plot(df) Thank you! Antje

Hi there, I have a question concerning the behaviour of the colouring with levelplot. (I hope, I manage to explain) If I give the parameters "at" and "col.regions" like this: at <- c(1,2,3,4,5,6) col.regions <- c("blue","blue","blue","yellow","yellow","yellow") Which color would have the value 3.5? I would

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 =

A few day ago, I was looking for an answer to my question but didn't get one. Anybody who can help now? Hello, I tried to use mle to fit a distribution(zero-inflated negbin for count data). My call is very simple: mle(ll) ll() takes the three parameters, I'd like to be estimated (size, mu and prob). But within the ll() function I have to judge if the current parameter-set gives a nice

Hello, I tried to use mle to fit a distribution(zero-inflated negbin for count data). My call is very simple: mle(ll) ll() takes the three parameters, I'd like to be estimated (size, mu and prob). But within the ll() function I have to judge if the current parameter-set gives a nice fit or not. So I have to apply them to observation data. But how does the method know about my observed

Hi there, I try to understand the usage of environments but I'm not sure if I get it. I wrote a test script like this: testenv <- new.env(environment()) myfun <- function(x) { print(testvar) testenv$testvar_2 <- 20 } environment(myfun) <- testenv testenv$testvar <- 10 myfun("hello") ls(envir = testenv) Now, I was wondering if there is any way to create new

Hello, I have a question how to reshape a given matrix to a data frame. # ---------------------------------- > a <- matrix(1:25, nrow=5) > a [,1] [,2] [,3] [,4] [,5] [1,] 1 6 11 16 21 [2,] 2 7 12 17 22 [3,] 3 8 13 18 23 [4,] 4 9 14 19 24 [5,] 5 10 15 20 25 > colnames(a) <- LETTERS[1:5] > rownames(a) <-

Hi there, I have a list of dataframes (generated by reading multiple files) and all dataframes are comparable in dimension and column names. They also have a common column, which, I'd like to use for merging. To give a simple example of what I have: df1 <- data.frame(c(LETTERS[1:5]), c(2,6,3,1,9)) names(df1) <- c("pos", "data") df3 <- df2 <- df1 df2$data

Hello, I guess the solution is rather simple but whatever I tried, I don't manage to get the result as I want to have it: I have several vectors of equal length in a list and I'd like to combine all first elements to a single string, all second elements to a single string, ..., all n-th elements to a single string. # Example code (how it should look like): t1 <- c(1,2,3) t2 <-

Hi there, as I'm not sure to understand the coloring levelplot uses, I'm looking for another easy way to create a heatmap like this: library(lattice) mat <- matrix(seq(1,5, length.out = 12), nrow = 3) mat[1,2] <- 3.5 my.at <- seq(0.5,5.5, length.out = 6) my.col.regions <- rainbow(5) graph <- levelplot(t(mat[nrow(mat):1, ] ), at = my.at, col.regions = my.col.regions)

Hi there, I have a barplot and the labels at the x-axis are strings, which are rotated by 90?. But now the sub-title of the barplot is in between these labels, which does not look very nice... Could anybody help me finding the parameter-setting to prevent this? par(mai=c(1.5,1,1,0.6)) barplot(data, las=2, ylim = c(0,plotMax+1), ylab = "Percentage", main = filename, sub = subtitle)

Hi there, assume that you have data with different sampling like d1 <- rnorm(100) d2 <- rnorm(150) now, I'd like to create two boxplots in one graph but each plot located at the sampling number at the x-axis. This, I can do with "at" l <- list(d1,d2) boxplot(l, at=c(length(d1), length(d2)), xlim=c(0,200) ) but both plots are very thin and I'd like to increase the

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