I have put the new package bindata to CRAN, which provides a method
for creating binary (i.e., 0-1-valued) random variables with
correlation structures by converting multivariate random variables to
binary variables.
The package includes a postscript file of a technical report
describing the method, here's the abstract:
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The generation of random variates from multivariate binary
distributions has not gained as much interest in the literature as,
e.g., multivariate normal or Poisson distributions. Binary variables
are important in many types of applications. Our main interest is in
the segmentation of marketing data, where data come from customer
questionnaires with ``yes/no'' questions. Artificial data provide a
valuable tool for the analysis of segmentation tools, because data
with known structure can be constructed to mimic situations from the
real world (Dolnicar et al. 1998). Questionnaire data can be highly
correlated, when several questions covering the same field are likely
to be answered similarly by a subject. In this paper we present a
computationally fast method to simulate multivariate binary
distributions with a given correlation structure. The implementation
of the algorithm in R, an implementation of the S statistical
language, is described in the appendix.
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--
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Friedrich Leisch
Institut f?r Statistik Tel: (+43 1) 58801 4546
Technische Universit?t Wien Fax: (+43 1) 504 14 98
Wiedner Hauptstra?e 8-10/1071 Friedrich.Leisch at ci.tuwien.ac.at
A-1040 Wien, Austria http://www.ci.tuwien.ac.at/~leisch
PGP public key http://www.ci.tuwien.ac.at/~leisch/pgp.key
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