Learn R Programming

proportion (version 2.0.0)

hypotestBAF6: Bayesain Hypothesis testing : Hypothesis 6: Theta < Theta1 Vs Theta > Theta2

Description

Bayesain Hypothesis testing : Hypothesis 6: Theta < Theta1 Vs Theta > Theta2

Usage

hypotestBAF6(n, th1, a1, b1, th2, a2, b2)

Arguments

n
- Number of trials from data
th1
- Hypothetical parameter for H1
a1
- Priors for hypothesis H1
b1
- Priors for hypothesis H1
th2
- Hypothetical parameter for H2
a2
- Priors for hypothesis H2
b2
- Priors for hypothesis H2

Value

A dataframe with
x
Number of successes
BaFa01
Bayesian Factor

Details

Computes Bayes factor under Beta-Binomial model for the model: \(p < p1\) Vs \(p > p2\) from the given number of trials n and for all number of successes \(x = 0, 1, 2......n \) We use the following guideline for reporting the results:
  • 1/3 <= BaFa01 < 1: Evidence against H0 is not worth more than a bare mention.
  • 1/20 <= BaFa01 < 1/3: Evidence against H0 is positive.
  • 1/150 <= BaFa01 < 1/20: Evidence against H0 is strong.
  • BaFa10 < 1/150: Evidence against H0 is very strong.
  • 1 <= BaFa01 < 3: Evidence against H1 is not worth more than a bare mention.
  • 3 <= BaFa01 < 20: Evidence against H1 is positive.
  • 20 <= BaFa01 < 150: Evidence against H1 is strong.
  • 150 <= BaFa01: Evidence against H1 is very strong.

References

[1] 2006 Ghosh M, Delampady M and Samanta T. An introduction to Bayesian analysis: Theory and Methods. Springer, New York

[2] 2014 Sakthivel S, Subbiah M and Ramakrishnan R Default prior approach for Bayesian testing of hypotheses involving single binomial proportion International Journal of Statistics and Analysis, 4 (2), 139 - 153

See Also

Other Hypothesis testing: hypotestBAF1x, hypotestBAF1, hypotestBAF2x, hypotestBAF2, hypotestBAF3x, hypotestBAF3, hypotestBAF4x, hypotestBAF4, hypotestBAF5x, hypotestBAF5, hypotestBAF6x

Examples

Run this code
n=10;th1=0.1; a1=1; b1=1; th2=0.9; a2=0.5; b2=0.5
hypotestBAF6(n,th1,a1,b1,th2,a2,b2)

Run the code above in your browser using DataLab