Abs Spurdle
2018-Dec-03 01:59 UTC
[R] [R-pkgs] Introducing empirical: Probability Distributions as Models of Data
hi all I would like to introduce my R package: empirical: Probability Distributions as Models of Data The description is: Computes continuous (not step) empirical (and nonparametric) probability density, cumulative distribution and quantile functions. Supports univariate, multivariate and conditional probability distributions, some kernel smoothing features and weighted data (possibly useful mixed with fuzzy clustering). Can compute multivariate and conditional probabilities. Also, can compute conditional medians, quantiles and modes. Notes: (1) I'm planning to support categorical variables in the future. (2) There are some problems with univariate models (but not multivariate), especially PDFs. (3) Contrary to what the name empirical suggests, currently multivariate models use kernel smoothing. (4) I'm interested in implementing a hybrid Kernel-Quantile method, which I suspect may be more robust to outliers. If I succeed, then I may rewrite the univariate implementation. The URL is: https://cran.r-project.org/package=empirical I've written a vignette which describes the package in more detail. It's URL is: https://cran.r-project.org/web/packages/empirical/vignettes/empirical.pdf kind regards Abs [[alternative HTML version deleted]] _______________________________________________ R-packages mailing list R-packages at r-project.org https://stat.ethz.ch/mailman/listinfo/r-packages
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