Dear R users, An updated version of the np package has recently been uploaded to CRAN (version 0.14-1).
The package is briefly described in a recent issue of Rnews (October, 2007, http://cran.r-project.org/doc/Rnews/Rnews_2007-2.pdf) for those who might be interested. A somewhat more detailed paper that describes the np package is forthcoming in the Journal of Statistical Software (http://www.jstatsoft.org) for those might be interested. A much more thorough treatment of the subject matter can be found in Li, Q. and J. S. Racine (2007), Nonparametric Econometrics: Theory and Practice, Princeton University Press, ISBN: 0691121613 (768 Pages) for those who might be interested (http://press.princeton.edu/titles/8355.html) Information on the np package: This package provides a variety of nonparametric (and semiparametric) kernel methods that seamlessly handle a mix of continuous, unordered, and ordered factor datatypes. We would like to gratefully acknowledge support from the Natural Sciences and Engineering Research Council of Canada (NSERC:www.nserc.ca), the Social Sciences and Humanities Research Council of Canada (SSHRC:www.sshrc.ca), and the Shared Hierarchical Academic Research Computing Network (SHARCNET:www.sharcnet.ca). Changes from version 0.13-1 to 0.14-1: * now use optim rather than nlm for minimisation in single index and smooth coefficient models * fixed bug in klein-spady objective function * regression standard errors are now available in the case of no continuous variables * summary should look prettier, print additional information * tidied up lingering issues with out-of-sample data and conditional modes * fixed error when plotting asymptotic errors with conditional densities * fixed a bug in npplot with partially linear regressions and plot.behavior='data' or 'plot-data' * maximum default number of multistarts is now set to 5 * least-squares cross-validation of conditional densities uses a new, faster algorithm * new, faster algorithm for least-squares cross-validation for both local-constant and local linear regressions. The estimator has changed somewhat: both cross-validation and the estimator use a method of shrinking towards the local constant estimator rather than the standard ridge approach that shrinks towards zero * optimised smooth coefficient code, added ridging * fixed bug in uniform CDF kernel * fixed bug where npindexbw would ignore bandwidth.compute = FALSE and compute bandwidths when supplied with a preexisting bw object * now can handle estimation out of discrete support. * summary would misreport the values of discrete scale factors which were computed with bwscaling = TRUE We are grateful to John Fox, Achim Zeilies, Roger Koenker, and numerous users for their valuable feedback which resulted in an improved version of the package. -- Jeffrey Racine & Tristen Hayfield. -- Professor J. S. Racine Phone: (905) 525 9140 x 23825 Department of Economics FAX: (905) 521-8232 McMaster University e-mail: [EMAIL PROTECTED] 1280 Main St. W.,Hamilton, URL: http://www.economics.mcmaster.ca/racine/ Ontario, Canada. L8S 4M4 `The generation of random numbers is too important to be left to chance' _______________________________________________ R-packages mailing list [EMAIL PROTECTED] https://stat.ethz.ch/mailman/listinfo/r-packages ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.