post.theta: Generates posterior samples of the parameters
In SurrogateBMA: Flexible Evaluation of Surrogate Markers with Bayesian Model Averaging
View source: R/SurrogateBMA_functions.R
post.theta R Documentation
Generates posterior samples of the parameters
Description
Provides a function to generate MCMC samples of p(theta_m | M = m, Data).
Usage
post.theta(Y, S, A, m, nmc = 500, prior.para = NULL)
Arguments
Y
S
A
m
nmc
prior.para
Value
a numeric matrix; each row contains a MC sample from the posterior of the parameters given a certain model.
Author(s)
Yunshan Duan
References
Duan, Y. and Parast, L., 2023. Flexible evaluation of surrogate markers with Bayesian model averaging. Statistics in Medicine.
SurrogateBMA documentation built on May 29, 2024, 8:55 a.m.
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View source: R/SurrogateBMA_functions.R
| post.theta | R Documentation |
Generates posterior samples of the parameters
Description
Provides a function to generate MCMC samples of p(theta_m | M = m, Data).
Usage
post.theta(Y, S, A, m, nmc = 500, prior.para = NULL)
Arguments
Y |
|
S |
|
A |
|
m |
|
nmc |
|
prior.para |
Value
a numeric matrix; each row contains a MC sample from the posterior of the parameters given a certain model.
Author(s)
Yunshan Duan
References
Duan, Y. and Parast, L., 2023. Flexible evaluation of surrogate markers with Bayesian model averaging. Statistics in Medicine.
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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