Dear R users, we would like to announce that on the CRAN a new package (SeleMix version 0.8.1) for selective editing is available.
This package includes functions for identification of outliers and influential errors in numerical data. For each unit, it provides also anticipated values (predictions) for both observed and non observed variables. The method is based on explicitly modelling both true (error-free) data and error mechanism through a two-component Gaussian mixture. Specifically, true data (first mixture component) are supposed to follow normal or log-normal distribution. We assume that only a subset of data (second mixture component) is affected by error and that the error mechanism is specified through a Gaussian random variable with zero mean vector and covariance matrix proportional to the covariance matrix of the true data distribution. We would appreciate any feedback Sincerely, Teresa Buglielli and Ugo Guarnera -- Teresa Buglielli Methods, Tools and Methodological Support Italian National Institute of Statistics bugli...@istat.it Ugo Guarnera Methods, Tools and Methodological Support Italian National Institute of Statistics guarn...@istat.it _______________________________________________ R-packages mailing list r-packa...@r-project.org 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.
