14_PD_categorical: Categorical Distributions

In bivariate: Bivariate Probability Distributions

Description

Bivariate categorical distributions.

Usage

gbvpmf (p)

Arguments

p	Numeric matrix of probabilities (or frequencies), preferably with row and column names.

Value

Self-referencing S4-based function objects.

Refer to Function Objects.

References

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

Note that the probhat package supports categorical distributions, and provides more tools.

See Also

Uniform
For uniform distributions.

Binomial and Poisson
For other probability distributions of discrete random variables.

Normal, Bimodal, Dirichlet and Nonparametric
For other probability distributions of continuous random variables.

Main Plotting Functions

Density Matrices

Examples

library (barsurf)

h <- matrix (sample (1:24), 4, 6)
rownames (h) <- LETTERS [1:4]
colnames (h) <- letters [1:6]

f <- gbvpmf (h)

plot (f)
plot (f, FALSE)

h [2, 1:4] / sum (h)
f (2, 1:4)
f ("B", c ("a", "b", "c", "d") )

bivariate documentation built on April 11, 2021, 9:06 a.m.