proportion (version 2.0.0)

empericalBAx: The empirical Bayesian approach for Beta-Binomial model given x

Description

The empirical Bayesian approach for Beta-Binomial model given x

Usage

empericalBAx(x, n, alp, sL, sU)

Arguments

x

- Number of successes

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

LEBAQ

- Lower limits of Quantile based intervals

UEBAQ

- Upper limits of Quantile based intervals

LEBAH

- Lower limits of HPD intervals

UEBAH

- Upper limits of HPD intervals

Details

Highest Probability Density (HPD) and two tailed intervals are provided for the required x (any one value from \( 0, 1, 2 ..n\)) 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: empericalBA, probPOSx, probPOS, probPREx, probPRE

Examples

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