31_distribution_sets: Distribution Sets

In probhat: Multivariate Generalized Kernel Smoothing and Related Statistical Methods

Description

Sets of distributions.
Note that distributions sets can also be produced by conditional CKS models.

NOTE THAT THESE OBJECTS ARE SUBJECT TO CHANGE, AND HAVE HAD LIMITED TESTING.

Usage

#categorical sets
#(grouped by a categorical variable)
ph4.pdfuv.gset.cks (g, x, ...)
ph4.cdfuv.gset.cks (g, x, ...)
ph4.qfuv.gset.cks (g, x, ...)
ph4.cdfuv.gset.el (g, x, ...)
ph4.qfuv.gset.el (g, x, ...)

#marginal sets
ph4.pdfuv.mset.cks (x, ..., bw, smoothness=1)
ph4.cdfuv.mset.cks (x, ..., bw, smoothness=1)
ph4.qfuv.mset.cks (x, ..., bw, smoothness=1)
ph4.cdfuv.mset.el (x, ...)
ph4.qfuv.mset.el (x, ...)

ph4.pdfmv.gset.cks (g, x, ...)

Arguments

g	A character vector, with the same length as x. Or an object which can be coerced to such a vector. If a list, its first element is used.
x	Vector (for categorical sets) or matrix (for marginal sets).
bw, smoothness	Bandwidth and smoothness parameters, same as pdfuv.cks, except that they can be an m-length vector, where m is the number of variables, equal to number of columns in x.
...	Other arguments for the corresponding constructor.

Details

PLEASE SET NOTES IN DESCRIPTION FIELD.

These functions construct distribution set objects, which are lists of probability distributions.

Value

A ph4.gset or ph4.mset object.

References

Refer to the vignette for an overview, references and better examples.

See Also

Succinct Constructors
Discrete Kernel Smoothing, Continuous Kernel Smoothing
Categorical Distributions, Empirical-Like Distributions

ph.plotf.ph4.gset, ph.plotf.ph4.mset

Examples

prep.ph.data ()

gs <- ph4.pdfuv.gset.cks (species, sepal.length)
ms <- ph4.qfuv.mset.el (trees2)

names (gs)
plot (gs)
plot (ms, nr=2, nc=2)

#distance matrix
pdist (gs)

plot (gs [[1]])

probhat documentation built on May 12, 2021, 5:08 p.m.