24_empirical-like_distributions: Empirical-Like Models

In probhat: Multivariate Generalized Kernel Smoothing and Related Statistical Methods

Description

Fit empirical-like probability distributions, from data.

NOTE THAT THESE OBJECTS ARE LIKELY TO BE CONVERTED TO S4 OBJECTS, IN THE NEAR FUTURE.
ALSO, NOTE THAT THEIR INTERNAL STRUCTURE (THAT IS, THEIR ATTRIBUTES/SLOTS), IS SUBJECT TO CHANGE.

IN PRINCIPLE, YOU SHOULD NOT ACCESS ATTRIBUTES/SLOTS, DIRECTLY.

Usage

cdfuv.el (x, ..., w)
qfuv.el (x, ..., w)

Arguments

x	Numeric vector of data. Also can be a single-column numeric matrix, preferably with a column name.
w	Optional numeric vector of weights.
...	Additional arguments not allowed.

Details

PLEASE SET NOTES IN DESCRIPTION FIELD.

Refer to the vignette for more information.

Value

Self-referencing function objects.

Refer to Runtime Function Objects

References

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

See Also

Succinct Constructors
Discrete Kernel Smoothing, Continuous Kernel Smoothing, Categorical Distributions

is.el, ph.printf.phmodel, ph.plotf.eluv

Examples

prep.ph.data ()

eFht <- qfuv.el (height)
eFht (c (0.25, 0.5, 0.75) )

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