bayes_error: Determine the unconditional error probabilities for a set of...
In BayesianPower: Sample Size and Power for Comparing Inequality Constrained Hypotheses
Description
Usage
Arguments
Value
Description
Determine the unconditional error probabilities for a set of simulated
Bayes factors.
Usage
1
bayes_error(BFs1, BFs2, bound1 = 1, bound2 = 1/bound1)
Arguments
BFs1
A vector. Simulated BF12 under H1 for a given n
BFs2
A vector. Simulated BF12 under H2 for a given n
bound1
A number. The boundary above which BF12 favors H1
bound2
A number. The boundary below which BF12 favors H2
Value
A named vector. The Type 1, Type 2, Decision error and Area of Indecision probabilities
and the median Bayes factors under H1 and H2
BayesianPower documentation built on July 1, 2020, 6:02 p.m.
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Description Usage Arguments Value
Description
Determine the unconditional error probabilities for a set of simulated Bayes factors.
Usage
1 | bayes_error(BFs1, BFs2, bound1 = 1, bound2 = 1/bound1)
|
Arguments
BFs1 |
A vector. Simulated BF12 under H1 for a given n |
BFs2 |
A vector. Simulated BF12 under H2 for a given n |
bound1 |
A number. The boundary above which BF12 favors H1 |
bound2 |
A number. The boundary below which BF12 favors H2 |
Value
A named vector. The Type 1, Type 2, Decision error and Area of Indecision probabilities and the median Bayes factors under H1 and H2
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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