wfabt: Bayes-optimal w-function
In fabCI: FAB Confidence Intervals
Description
Usage
Arguments
Details
Author(s)
Description
Compute Bayes optimal w-function
Usage
1
wfabt(theta, mu, t2, s20, nu0, n, alpha)
Arguments
theta
value of theta being tested
mu
prior mean of theta
t2
prior variance of theta
s20
prior parameter for population variance
nu0
prior parameter for population variance
n
sample size
alpha
level of test
Details
Internal function for fabtCI. This function computes the
value of w that minimizes the acceptance probability of a
biased level-alpha test under a specified prior
predictive distribution.
Author(s)
Peter Hoff
fabCI documentation built on Jan. 7, 2021, 5:09 p.m.
R Package Documentation
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Description Usage Arguments Details Author(s)
Description
Compute Bayes optimal w-function
Usage
1 | wfabt(theta, mu, t2, s20, nu0, n, alpha)
|
Arguments
theta |
value of theta being tested |
mu |
prior mean of theta |
t2 |
prior variance of theta |
s20 |
prior parameter for population variance |
nu0 |
prior parameter for population variance |
n |
sample size |
alpha |
level of test |
Details
Internal function for fabtCI. This function computes the value of w that minimizes the acceptance probability of a biased level-alpha test under a specified prior predictive distribution.
Author(s)
Peter Hoff
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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