similar to: RE: packaged datasets in .csv format (David Firth)

Is there a straightforward way to convert character information from decimal representation to the octal one used by R? I'd like something like a function ascii(number,base=10), such that > ascii(91) [1] "\133" I can easily do the mapping from 91 to 133, but what is a good way to operate on 133 to deliver "\133"? Would a lookup table be a better solution? David

I am making my first attempts at using some Fortran code with R, and so far it's going OK. To print from my Fortran programs, it seems I need subroutines dblepr, realpr and intpr. From the excellent "Writing R Extensions" document: "Three subroutines are provided to ease the output of information from FORTRAN code. subroutine dblepr(label, nchar, data, ndata)

I am having a little problem in relation to sending output to the R Console window, when a function is called by pushing a button in a Tk window. Actually there seem to be two components to the problem: -- the R prompt does not re-appear until <return> is pressed -- text output to the R Console window *disappears* after <return> is pressed The following, in R 1.1.1 under

I suppose this could be described as a feature (it seems to be similar in S-Plus), but it looks to me more like a bug. Why can't the assignment below to a row of "emptyframe" (or "anotherframe") be made? This with R --vanilla (version info below). Regards -- David David Firth Phone +44 1865 278544 Nuffield College Fax +44 1865

Hi David, I hope all is well w/ you. Co-operation beetwen R and Ox would be most welcome. A possible problem lies in the fact that, although free for academic use, Ox is not open source. I too have been using Ox for computer-intensive programming. I also code some of my programs in C, but I always try Ox first, and in most cases it is efficient enough. For details, see

Is there some neat way of storing the printed representation of an object as a character string? I can see how it could be done via disk using sink() and then scan(), but that's ugly. Something like Lisp-Stat's "with-output-to-string" macro perhaps? David Firth Phone +44 1865 278544 Nuffield College Fax +44 1865 278621 Oxford OX1

I am aware of the nice R package "logspline", which does smooth density estimation from interval-censored data (that is, values that are known to lie in a specified interval rather than known exactly). Function logspline.fit uses a maximum penalized likelihood method, with the penalty related to the number of knots used in a cubic regression-spline fit. I need to be able to do some

Hi everybody, I have the following problem. I have a vector containing character elements, such as: list = c("aa","bb","cc","dd","ee") I want to create an index which identifies the elements that are different from, e.g. "aa" and "bb". When I do the following: jj = list!="aa" & list!="bb" > jj

This is some kind of follow-up to my previous posts. I have further improved the speed of my program 6 times by eliminating all the apply(). It turns out that apply is slow, is slower than direct loop, it is an order slower than a matrix operation alternative. Here is one example. The first apply version runs 19 seconds, the second loop version runs 13 seconds, the third matrix version runs 1

*The Jenner Institute is seeking to appoint an outstanding Bioinformatician to run a Transcriptomics Core Facility at the Jenner Institute and to identify, develop and integrate bioinformatics resources into the research programmes of the institute. You will be based at the Jenner Institute in the Old Road Campus Research Building, Headington, Oxford and working in conjunction with Gilean

I've posted a sample file for estimating loglinear models for square tables (mobility models) at http://www.xs4all.nl/~jhckx/mcl/R/ Comments and suggestions are welcome. John Hendrickx

I am trying to bootstrap the parameters for a model that is estimated through the optim() function and find that when I make the call to boot, it runs but returns the exact same estimate for all of the bootstrap estimates. I managed to replicate the same problem using a glm() model but was able to fix it when I made a call to the variables as data frame by their exact names. But no matter how I

Hi, It works for me to import spss datasets via library(foreign) with read.spss or via library Hmisc by (spss.get). But no matter which way I do import the data, user-defined missings from Spss are always lost. (it makes no difference if there are a single value, a range, or any combination of them. They are always ignored). Is there any way in R to find out if any value was user-defined missing

Full_Name: David Firth Version: 1.2.3 OS: Windows NT4 Submission from: (NULL) (163.1.103.107) Two things that look like bugs: 1. RCMD INSTALL does not seem to cope with quotes in the Windows path. With my path set to PATH="C:\R\Rtools";"C:\R\rw1023\bin";C:\Perl\bin\;C:\WINNT\system32;C:\WINNT;C:\ mingw2\bin I get, for example, C:\R>RCMD INSTALL boot RCMD

I want to set up a simple Tk dialog interface to a function in R, such that when the "OK" button is pressed, the dialog window is destroyed and then R does its work on the data/parameters/whatever that were entered in the dialog. The function "test" below is a simple prototype. My problem: upon running test() and hitting "OK", R does its work (ie, computes

I have a data set w/ an ordinal response taking on one of 10 categories. I am considering using polr to fit a cumulative logits model. I previously fit the model in SAS (using proc logistic) which provides a test for the proportional odds assumption (p < 0.001 for the test). Are there simple diagnostic plots that can be used to look at the validity of this assumption and possibly help w/

I am looking for examples of code that demonstrates the fine tuning of the strip panels in lattice graphics and uses plotmath characters. The code for the graphic is as follows: xyplot(lagy ~ n | rho1 * rho2, data= data, layout=c(2,6), span = 1, xlab = "Sample Size", ylab = "Bias in the Coefficient for the Lag of X", type = "o") rho1 is a four level factor

Q: Is there an easy way to plot log histograms? The command "hist" draws a standard histogram with observed frequency on the y-axis. I would like to be able to draw the log frequency on the y-axis, but I can't see whether I can use "hist" for this. The purpose of such a plot is to see whether data are normal or Laplace or something else. - and the same question for

Hi, How can I import user-defined missings from Spss? It works for me to import spss datasets via library(foreign) with read.spss or via library Hmisc by (spss.get). But no matter which way I do import the data, user-defined missings from Spss are always lost. (it makes no difference if there are a single value, a range, or any combination of them. They are always ignored). Is there any way in

Dear all, Last autumn there was some discussion on the list of the warning Warning message: fitted probabilities numerically 0 or 1 occurred in: (if (is.empty.model(mt)) glm.fit.null else glm.fit)(x = X, y = Y, when fitting binomial GLMs with many 0 and few 1. Parts of replies: "You should be able to tell which coefficients are infinite -- the coefficients and their standard errors will