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proportion (version 2.0.0)

probPRE: 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

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

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

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

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

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