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proportion (version 2.0.0)

empericalBA: The empirical Bayesian approach for Beta-Binomial model

Description

The empirical Bayesian approach for Beta-Binomial model

Usage

empericalBA(n, alp, sL, sU)

Arguments

n
- Number of trials
alp
- Alpha value (significance level required)
sL
- Lower support for MLE optimization
sU
- Upper support for MLE optimization

Value

A dataframe with
x
- Number of successes (positive samples)
pomean
- Posterior mean
LBAQ
- Lower limits of Quantile based intervals
UBAQ
- Upper limits of Quantile based intervals
LBAH
- Lower limits of HPD intervals
UBAH
- Upper limits of HPD intervals

Details

Highest Probability Density (HPD) and two tailed intervals are provided for all \(x = 0, 1, 2 ..n\) based on empirical Bayesian approach for Beta-Binomial model. Lower and Upper support values are needed to obtain the MLE of marginal likelihood for prior parameters.

References

[1] 1998 Lehmann EL and Casella G Theory of Point Estimation, 2nd ed Springer, New York

See Also

Other Miscellaneous functions for Bayesian method: empericalBAx, probPOSx, probPOS, probPREx, probPRE

Examples

Run this code
sL=runif(1,0,2)				#Lower and upper of Support for MLE optimization
sU=runif(1,sL,10)
n= 5; alp=0.05
empericalBA(n,alp,sL,sU) 

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