sbinom: Abstract definitions of distributions

In bbmle: Tools for General Maximum Likelihood Estimation

Abstract definitions of distributions

Description

Functions returning values for summary statistics (mean, median, etc.) of distributions

Usage

sbeta(shape1, shape2)
sbetabinom(size, prob, theta)
sbinom(size, prob)
snbinom(size, prob, mu)
snorm(mean, sd)
spois(lambda)
slnorm(meanlog, sdlog)

Arguments

prob	probability as defined for dbinom, dnbinom, or beta-binomial distribution (dbetabinom in the emdbook package)
size	size parameter as defined for dbinom or dbetabinom in the emdbook package, or size/overdispersion parameter as in dnbinom
mean	mean parameter as defined for dnorm
mu	mean parameter as defined for dnbinom
sd	standard deviation parameter as defined for dnorm
shape1	shape parameter for dbeta
shape2	shape parameter for dbeta
lambda	rate parameter as defined for dpois
theta	overdispersion parameter for beta-binomial (see dbetabinom in the emdbook package)
meanlog	as defined for dlnorm
sdlog	as defined for dlnorm

Value

title	name of the distribution
[parameters]	input parameters for the distribution
mean	theoretical mean of the distribution
median	theoretical median of the distribution
mode	theoretical mode of the distribution
variance	theoretical variance of the distribution
sd	theoretical standard deviation of the distribution

Note

these definitions are tentative, subject to change as I figure this out better. Perhaps construct functions that return functions? Strip down results? Do more automatically?

Author(s)

Ben Bolker

See Also

dbinom, dpois, dnorm, dnbinom

Examples

  sbinom(prob=0.2,size=10)
  snbinom(mu=2,size=1.2)

bbmle documentation built on May 29, 2024, 11:02 a.m.