Bayesian Pearson Correlation: Prior Distribution
You can specify the value c for the prior
p(ρ)∝(1−ρ2)c.
Note: Many applied researchers may question the need to specify a prior. Reference priors
minimize the concern where the prior is generally overwhelmed as the data increases. When
informative prior information is specified, Bayesian methods can effectively use the information.
The requirement to specify a prior should not be viewed as a deterrent to using Bayesian
analysis.
- Uniform (c = 0)
- When selected the uniform prior is used.
- Jeffreys (c = -1.5)
- When selected, a non-informative prior distribution is used.
- Set custom c value
- When selected, you can specify a custom c value. Any single real number is allowed.