similar to: using rbind() on multiple objects at once

Participants in the R User Conference, useR! 2010, July 21-23, (http://R-project.org/useR-2010) will each receive a t-shirt, thanks to the sponsorship of Mango Solutions (http://www.mango-solutions.com/). This email is a call for designs for the front of the t-shirt. The design should be made using a single color of your choice. The design should be in the form of a high-resolution (at least

Hello, I created an array to hold the results of a series of simulations I'm running: d.eta <- array(0,dim=c(3,3,200)) <simulation goes here and populates the array but it's not important> Then I tried to save the results using this: save(d.eta,file="D:/Simulation Results/sim 9-23-11 deta") When I later tried to reload them using this: d.eta <-

Hi, All: What tools exist for diagnosing singular gradient problems with 'nls'? Consider the following toy example: DF1 <- data.frame(y=1:9, one=rep(1,9)) nlsToyProblem <- nls(y~(a+2*b)*one, DF1, start=list(a=1, b=1), control=nls.control(warnOnly=TRUE)) Error in nlsModel(formula, mf, start, wts) : singular gradient matrix at initial

As part of my work, I am trying to append matrices onto data frames. Naively I assumed that when rbinding a data.frame and matrix, the matrix would be coerced and appended, keeping the names from the data frame. Clearly, I am not fully understanding the process by which rbind works. Example code: > A<-data.frame(1,1,1); names(A)=letters[1:3] ; B<-matrix(0,2,3) > rbind(A,B)

Dear R-help gurus (and T.Yee, the VGAM maintainer) - I've been banging my head against the keyboard for too long now, hopefully someone can pick up on the errors of my ways... I am trying to use optim to fit a zero-inflated negative binomial distribution. No matter what I try I can't get optim to recognize my initial parameters. I think the problem is that dnbinom allows either

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

#I want to "merge" or "join" 2 dataframes (df1 & df2) into a 3rd (mydf). I want the 3rd dataframe to contain 1 row for each row in df1 & df2, and all the columns in both df1 & df2. The solution should "work" even if the 2 dataframes are identical, and even if the 2 dataframes do not have the same column names. The rbind.fill function seems to work. For

I am using rbind to concatenate two dataframes, but after the rbind I get a strange "double" index. I am using rbind a number of times to make one large dataset. Is there a way to prevent the "double" index? Or is there some other way to concatenate the data (it looks like merge only works by columns)? Here is an example of the "double" index.

Hi I installed R 2.2.0 from source and I have the packages for tcl and tk installed on my system, but the package tcltk says, when I try to load the library tcltk: Tcl/Tk support is not available on this system. Are there any settings / variables which I have to set so that R recognises that Tcl/Tk support is installed on the system? Rainer -- NEW TELEPHONE NUMBER Tel: +27 - (0)72 808

Hi all, I am doing some clustering and the clustered results are presented in a "pairs" plot showing 4 clusters... I made the data points belong to 4 different clusters displaying different colors. Now I want to select the best clustered class, how can I click on the data point, and the program returns the index of that cluster(its class number, or color number)? Also, if I would

How can I write a text, such as a result of a function or an explanation to a graphic device? When I try plot, I'm unable to reduce the axes. Greetings torsten

Dear R-users, I would like to process some spectroscopic data with R, and I was hoping some people might have some example code on how to do this. I would like to be able to do the following things: * Detect outlier-spectra -> This can be done by using scoreplot from the pls package * Determine the range of the spectrum to be used -> For this, I should be able to calculate the regression

I'm not sure if there are better methods to create objects such as dataframes with other than rbind function. II usually combine a data.frames created at each loop with a rbind(), specially when I don't know the dimension of the data.frame that will be created. Binding the new to an existing data.frame seems to be the easiest way to build an object that assemble data in a loop.

Full_Name: Lutz Prechelt Version: 2.4.1 OS: Windows XP Submission from: (NULL) (160.45.111.67) I stack a number of data.frames using rbind. Each of these dataframes has a column 'authorname', which is a factor and a column author = unclass(authorname) as piecewise pseudonyms. When using rbind to stack these dataframes, R warns about invalid factor levels and inserts all NAs in the author

Hi! I'm translating some code from Matlab to R and I found a problem. I need to translate Matlab's function 'lsqnonlin' (http://www-ccs.ucsd.edu/matlab/toolbox/optim/lsqnonlin.html) into R, and at the beginning I thought it would be the same as R's 'optim'. But then I looked at the definition of 'lsqnonlin' and I don't quite see how to make

Take the following code: foo <- list() foo[[1]] <- list(a=1, b=2) foo[[2]] <- list(a=11, b=22) foo[[3]] <- list(a=111, b=222) result <- do.call(rbind, foo) result[,'a'] In this case, result[,'a'] shows a list. Is there a more elegant way such that result is a "regular" matrix of vectors? I imagine there are manual ways of going about this, but I was

Dear All, I am trying to find MLE by using "OPTIM" function. Difficult in differentiating some parameter in my objective function, I would like to use the returned hessian matrix to yield an estimate of Fisher's Information matrix. My question: Since the hessian is calculated by numerical differentiate, is it a reliable estimate? Otherwise I would have to do a lot of work to

Hi I have a square matrix Ainv of size N-by-N where N ~ 1000 I have a rectangular matrix H of size N by n where n ~ 4. I have a vector d of length N. I need X = solve(t(H) %*% Ainv %*% H) %*% t(H) %*% Ainv %*% d and H %*% X. It is possible to rewrite X in the recommended crossprod way: X <- solve(quad.form(Ainv, H), crossprod(crossprod(Ainv, H), d)) where quad.form() is a little

Hello everybody, if I try to (r)bind a number of large dataframes I run out of memory because R wastes memory and seems to "forget" to release memory. For example I have 10 files. Each file contains a large dataframe "ds" (3500 cols by 800 rows) which needs ~20 MB RAM if it is loaded as the only object. Now I try to bind all data frames to a large one and need more than

Hello, I have been using read.table to read data files into R, then rbind to combine them into one table. The column headings are all identical, so it should be straightforward, and it seems to be working well so far. My question is: What is the maximum number of tables that can be combined with rbind? Is it driven by the number of rows in the tables, by a constraint with the syntax of rbind