bivariate (version 0.7.0)

13_PD_poisson: Poisson Distributions

Description

Bivariate Poisson distributions.

Usage

pbvpmf (lambda.1, lambda.2, lambda.3)
pbvcdf (lambda.1, lambda.2, lambda.3)
pbvpmf.2 (mean.X, mean.Y, cov)
pbvcdf.2 (mean.X, mean.Y, cov)

Arguments

lambda.1, lambda.2, lambda.3

Positive numeric values, giving the first, second and third lambda parameters.

mean.X, mean.Y

Suitable numeric values, giving the mean of X and Y. Note that their means equal their variances.

cov

Suitable numeric value, giving the covariance of X and Y.

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.

See Also

Uniform For uniform distributions.

Binomial and Categorical 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

# NOT RUN {
f <- pbvpmf (10, 10, 0)

plot (f)
f (5, 5)
# }