probhat (version 0.4.1)

31_distribution_sets: Distribution Sets

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.

Value

A ph4.gset or ph4.mset object.

Details

PLEASE SET NOTES IN DESCRIPTION FIELD.

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

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

# NOT RUN {
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]])
# }