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.


Reference manual

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0.4.1 by Abby Spurdle, 3 months ago

Browse source code at

Authors: Abby Spurdle

Documentation:   PDF Manual  

Task views:

GPL (>= 2) license

Imports barsurf, kubik

Depends on methods

Suggests bivariate, fclust, scatterplot3d

See at CRAN