EstMLEBetaBin: Estimating the shape parameters a and b for Beta-Binomial...

In fitODBOD: Modeling Over Dispersed Binomial Outcome Data Using BMD and ABD

Estimating the shape parameters a and b for Beta-Binomial Distribution

Description

The functions will estimate the shape parameters using the maximum log likelihood method and moment generating function method for the Beta-Binomial distribution when the binomial random variables and corresponding frequencies are given.

Usage

EstMLEBetaBin(x,freq,a,b,...)

Arguments

x	vector of binomial random variables.
freq	vector of frequencies.
a	single value for shape parameter alpha representing as a.
b	single value for shape parameter beta representing as b.
...	mle2 function inputs except data and estimating parameter.

Details

a,b > 0

x = 0,1,2,...

freq \ge 0

NOTE : If input parameters are not in given domain conditions necessary error messages will be provided to go further.

Value

EstMLEBetaBin here is used as a wrapper for the mle2 function of bbmle package therefore output is of class of mle2.

References

\insertRef

young2008poolingfitODBOD \insertReftrenkler1996continuousfitODBOD \insertRefhughes1993usingfitODBOD

See Also

mle2

Examples

No.D.D <- 0:7        #assigning the random variables
Obs.fre.1 <- c(47,54,43,40,40,41,39,95)   #assigning the corresponding frequencies

#estimating the parameters using maximum log likelihood value and assigning it
estimate <- EstMLEBetaBin(No.D.D,Obs.fre.1,a=0.1,b=0.1)

bbmle::coef(estimate)   #extracting the parameters

#estimating the parameters using moment generating function methods
EstMGFBetaBin(No.D.D,Obs.fre.1)

fitODBOD documentation built on April 4, 2025, 4:13 a.m.