empirical: Probability Distributions as Models of Data

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.

Version: 0.2.0
Depends: graphics, stats
Imports: barsurf
Suggests: intoo, bivariate, fclust, mgcv, gam, moments
Published: 2018-12-02
Author: Abby Spurdle
Maintainer: Abby Spurdle <spurdle.a at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://sites.google.com/site/asrpws
NeedsCompilation: no
CRAN checks: empirical results


Reference manual: empirical.pdf
Vignettes: Probability Distributions as Models of Data
Package source: empirical_0.2.0.tar.gz
Windows binaries: r-devel: empirical_0.2.0.zip, r-release: empirical_0.2.0.zip, r-oldrel: empirical_0.2.0.zip
OS X binaries: r-release: empirical_0.2.0.tgz, r-oldrel: empirical_0.2.0.tgz
Old sources: empirical archive

Reverse dependencies:

Reverse suggests: bivariate


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