expValBb: Expected value of a beta binomial distribution.

In dbd: Discretised Beta Distribution

Description

Calculate the expected value (theoretical mean) of a random variable having a beta binomial distribution.

Usage

expValBb(mo,...)
## S3 method for class 'mleBb'
expValBb(mo,...)
## Default S3 method:
expValBb(mo, size, ...)

Arguments

mo	For the "mleBb" method this argument is an object of class "mleBb" as returned by mleBb(). For the default method it is a numeric scalar, between 0 and 1, playing the role of m (which may be interpreted as the “success” probability. (See the help for dbetabinom().)
size	Integer scalar specifying the upper limit of the “support” of the beta binomial distribution under consideration. The support is the set of integers {0, 1, ..., size}. (See the help for dbetabinom().)
...	Not used.

Details

For the "mleBb" method, the single argument should really be called (something like) “object” and for the default method the first argument should be called m. However the argument lists must satisfy the restrictions that “A method must have all the arguments of the generic, including ... if the generic does.” and “A method must have arguments in exactly the same order as the generic.”

For the "mleBb" method, the values of m and size are extracted from the attributes of mo.

The expected value of a beta binomial distribution is trivial to calculate “by hand”. These functions are provided for convenience and to preserve parallelism with the db distribution.

Value

Numeric scalar equal to the expected value of a beta binomial distributed random variable with the given parameters.

Author(s)

Rolf Turner [e-mail]

See Also

expValDb() varDb() varBb()

Examples

   expValBb(0.3,15)
   X   <- hmm.discnp::Downloads
   fit <- mleBb(X,size=15)
   expValBb(fit)

dbd documentation built on Aug. 19, 2021, 5:07 p.m.