probPRE: The Predicted probability - Bayesian approach

In RajeswaranV/proportion: Inference on Single Binomial Proportion and Bayesian Computations

The Predicted probability - Bayesian approach

Description

The Predicted probability - Bayesian approach

Usage

probPRE(n, m, a1, a2)

Arguments

n	- Number of trials from data
m	- Future :Number of trials
a1	- Beta Prior Parameters for Bayesian estimation
a2	- Beta Prior Parameters for Bayesian estimation

Details

Computes posterior predictive probabilities for the required size of number of trials m from the given number of trials n for the given parameters for Beta prior distribution

Value

A matrix of probability values between [0,1]

predicted_probability	- The predicted probability
0:n	The number of columns based on the value of n

References

[1] 2002 Gelman A, Carlin JB, Stern HS and Dunson DB Bayesian Data Analysis, Chapman & Hall/CRC

See Also

Other Miscellaneous functions for Bayesian method: empericalBAx(), empericalBA(), probPOSx(), probPOS(), probPREx()

Examples

n=10; m=5; a1=0.5; a2=0.5
probPRE(n,m,a1,a2)

RajeswaranV/proportion documentation built on June 17, 2022, 9:11 a.m.