gMLE.bb {BayesGOF} R Documentation

## Beta-Binomial Parameter Estimation

### Description

Computes type-II Maximum likelihood estimates \hat{\alpha} and \hat{\beta} for Beta prior g\simBeta(\alpha,\beta).

### Usage

gMLE.bb(success, trials, start = NULL, optim.method = "default",
lower = 0, upper = Inf)


### Arguments

 success Vector containing the number of successes. trials Vector containing the total number of trials that correspond to the successes. start initial parameters; default is NULL which allows function to determine MoM estimates as initial parameters. optim.method optimization method in optim()stats. lower lower bound for parameters; default is 0. upper upper bound for parameters; default is infinity.

### Value

 estimate MLE estimate for beta parameters. convergence  Convergence code from optim(); 0 means convergence. loglik Loglikelihood that corresponds with MLE estimated parameters. initial Initial parameters, either user-defined or determined from method of moments. hessian Estimated Hessian matrix at the given solution.

### Author(s)

data(rat)
rat.mle <- gMLE.bb(rat$y, rat$N)$estimate rat.mle ### MoM estimate of alpha and beta rat.mom <- gMLE.bb(rat$y, rat$N)$initial