similar to: QCA version 1.0-4 released

Dear All, I have just uploaded a new version of the QCA (Qualitative Comparative Analysis) on CRAN, and it will be propagated in a couple of days. This is version 1.0-0 ("Easter edition") of the package, straight from the previous version 0.6-5, and it represent a major re-write of the package in order to accomodate fuzzy-sets. I am pleased to welcome Alrik Thiem as a co-author of this

Dear All, I have just uploaded a new version of the QCA (Qualitative Comparative Analysis) on CRAN, and it will be propagated in a couple of days. This is version 1.0-0 ("Easter edition") of the package, straight from the previous version 0.6-5, and it represent a major re-write of the package in order to accomodate fuzzy-sets. I am pleased to welcome Alrik Thiem as a co-author of this

Hi, A new version of the QCA package (0.6-0) was submitted to CRAN. This is a major improvement, now working with multi-valued data (previous versions accepted binary data only). The "classical" function qmcc() still accepts only binary data, but the enhanced function eqmcc() is now ready for mvQCA. The QCA package performs the Quine-McCluskey algorithm for Qualitative Comparative

Hi, A new version of the QCA package (0.6-0) was submitted to CRAN. This is a major improvement, now working with multi-valued data (previous versions accepted binary data only). The "classical" function qmcc() still accepts only binary data, but the enhanced function eqmcc() is now ready for mvQCA. The QCA package performs the Quine-McCluskey algorithm for Qualitative Comparative

Dear r-devel, I am trying to automatically check if two successive versions of a package have the same results (i.e. code not broken), by parsing the example sections for each function against a previously tested version. While trying to replicate the code from example(), I am facing an error related with te "index.search" function (line 7 in the example() code). This is the code I am

Dear list members, A new version of the QCA package is now on CRAN. The QCA package implements the Quine-McCluskey algorithm for boolean minimizations, according to the Qualitative Comparative Analysis. Along with the additional improvements in version 0.3-1 (soon to be released on CRAN), this code is about 100 times faster than the previous "major" release (0.2-6). It can now

Dear list members, A new version of the QCA package is now on CRAN. The QCA package implements the Quine-McCluskey algorithm for boolean minimizations, according to the Qualitative Comparative Analysis. Along with the additional improvements in version 0.3-1 (soon to be released on CRAN), this code is about 100 times faster than the previous "major" release (0.2-6). It can now

Dear list members, I am pleased to let you know that R met with QCA - Qualitative Comparative Analysis. This package has a few functions that implement the Quine-McCluskey algorithm, adapted to social sciences by Charles Ragin (as describes in his book from 1987 "The Comparative Method"). Future versions of this package will have more functions to address the fuzzy-set minimization

QCA implements the Qualitative Comparative Analysis using a boolean minimization algorithm for data coded with presence/absence of the causal conditions that affects a phenomenon of interest. This new release has an experimental function that obtains the same exact solutions as the main minimization function, using a shortcut instead of the classical complete and exhaustive algorithm. This

Dear All, I have just submitted a new version of the QCAGUI package on CRAN, it should be propagated in a couple of days. This version is nothing but a quick update to the latest Rcmdr base package, and works (as usual) with the QCA package up to version 0.6-5 For the later versions of the QCA package, I will start adapting the GUI in the shortest time possible. Best wishes, Adrian -- Adrian

Dear R-help list, Part of a program I wrote seem to take a significant amount of time, therefore I am looking for an alternative approach. In order to explain what is does: - the input is a sorted vector of integer numbers - some higher numbers may be derived (using a mathematical formula) from lower numbers, therefore they should be eliminated - at the end, the vector should contain only

Dear R-devel, I'm trying to validate the results from a C function, against a (trial and tested) older R function. For reasons unknown to me, the C function seems to give different result sometimes at each trial, even with the very same data. These are the relevant outputs from R: > library(QCA) Loading required package: lpSolve > benchmark <- function(x, y) { + index <- 0

Dear list, Just upgraded to MacOS Mavericks, fresh install of R 3.0.2 and trying to install a previous version of my QCA package (the most recent one source file, which passed the R CMD check --as-cran with R 3.0.1) I seem to have some difficulties in the C code, apparently it doesn't find some headers (please see below): ============ $ R CMD INSTALL --no-multiarch

Dear list, I have a vector of numbers, let's say: myvec <- c(2, 8, 24, 26, 51, 57, 58, 78, 219) My task is to reduce this vector to non-reducible numbers; small numbers can cross-out some of the larger ones, based on a function let's say called reduce() If I apply the function to the first element 2, my vector gets shorted to: > (myvec <- reduce(myvec[1])) [1] 2 24 51

Dear list members, I'm pleased to let you know there's a new package on CRAN called QCAGUI, a graphical user interface for the QCA package. This is a stripped down version of John Fox's Rcmdr package, plus a couple of menus for QCA. My thanks to John Fox for his encouragement and advice. Regards, Adrian -- Adrian DUSA Romanian Social Data Archive 1, Schitu Magureanu Bd 050025

Dear All, I assume this is an R-devel issue, apologies if I missed something obvious. I have a dataframe where the row names are country codes, based on ISO 3166, something like this: ------------ "v1" "v2" "UK" 1 2 "NA" 2 3 ------------ It happens that "NA" is the country code for "Namibia", and that creates problems on

Dear R devel, Apologies for these (most probably trivial) questions, doing my first attempt to call C from R (and actually learning C in the process). I need to pass a matrix to C, and after reading R-exts.pdf (many times), I was unable to find how to handle matrices at C-level... except for, what probably is the answer, that matrices are in fact vectors with dimensions. This is a sample code I

Dear R-devel, I am now at a debugging phase, and would like to inspect the (individual) values in an arbitrary R vector. It should be simple, but after hours of reading I am simply unable to find the right information. A possible C code is: ????????????????? # include <R.h> # include <Rinternals.h> # include <R_ext/Rdynload.h> SEXP foo(SEXP x) // where x is a vector passed by

Dear devels, I need to create a (short) vector in C, which contains potentially very large numbers, exponentially to the powers of 2. This is my test example: lgth = 35; int power[lgth]; power[lgth - 1] = 1; for (j = 1; j < lgth; j++) { power[lgth - j - 1] = 2*power[lgth - j]; } Everything works ok until it reaches the limit of 2^32: power: 1, 2, 4, 8, 16, 32, 64, 128, 256, 512, 1024,

Dear list, On a follow up from my previous email, I am now trying to allocate vectors of length larger than 32-bit in C. >From the R internals documentation, I read that: "The sxpinfo header is defined as a 32-bit C structure..." and "A SEXPREC is a C structure containing the 32-bit header..." The question is: does the INTSXP allow vectors larger than 32-bit? A test