probhat: Multivariate Generalized Kernel Smoothing and Related Statistical Methods

Probability mass functions (PMFs), probability density functions (PDFs), cumulative distribution functions (CDFs) and quantile functions, mainly via (optionally bounded/truncated) kernel smoothing. In the continuous case, there's support for univariate, multivariate and conditional distributions, including distributions that are both multivariate and conditional. Refer to the book "Kernel Smoothing" by Wand and Jones (1995), whose methods are generalized by the methods here. Also, supports categorical distributions, mixed conditional distributions (with mixed input types) and smooth empirical-like distributions, some of which, can be used for statistical classification. There are extensions for computing distance matrices (between distributions), multivariate probabilities, multivariate random numbers, moment-based statistics and mode estimates.

Version: 0.4.1
Depends: methods
Imports: barsurf, kubik
Suggests: bivariate, fclust, scatterplot3d
Published: 2021-05-12
Author: Abby Spurdle
Maintainer: Abby Spurdle <spurdle.a at>
Contact: Primary <>, Secondary <>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
In views: Distributions
CRAN checks: probhat results


Reference manual: probhat.pdf
Vignettes: Multivariate Generalized Kernel Smoothing and Related Statistical Methods
Kernel Reference Sheet
Package source: probhat_0.4.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): probhat_0.4.1.tgz, r-release (x86_64): probhat_0.4.1.tgz, r-oldrel: probhat_0.4.1.tgz
Old sources: probhat archive

Reverse dependencies:

Reverse suggests: barsurf, bivariate


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