proportion (version 2.0.0)

probPOSx: Bayesian posterior Probabilities

Description

Bayesian posterior Probabilities

Usage

probPOSx(x, n, a, b, th)

Arguments

x

- Number of successes

n

- Number of trials

a

- Prior Parameters

b

- Prior Parameters

th

- Theta value seeking Pr(Theta/X < th)

Value

A dataframe with

x

Number of successes

PosProb

Posterior probability

Details

Computes probability of the event \(p < p0\) (p0 is specified in [0, 1]) based on posterior distribution of Beta-Binomial model with given parameters for prior Beta distribution for all \(x = 0, 1, 2......n \) where n is the number of trials

References

[1] 2002 Gelman A, Carlin JB, Stern HS and Dunson DB Bayesian Data Analysis, Chapman & Hall/CRC [2] 2006 Ghosh M, Delampady M and Samanta T. An introduction to Bayesian analysis: Theory and Methods. Springer, New York

See Also

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

Examples

x=5; n=5;  a=0.5; b=0.5; th=0.5;
probPOSx(x,n,a,b,th)