derive_BGe_posterior_probabilities: Compute the posterior probabilities of L_k -> T_i -> T_j for...
In igbucur/BFCS: Bayes Factors for Covariance Structures
Description
Usage
Arguments
Value
Examples
Description
Compute the posterior probabilities of L_k -> T_i -> T_j for a simulated GRN
using bfcs::compute_BGe_score_vectorized.
Usage
1
derive_BGe_posterior_probabilities(GRN, prior = uniform_prior_GRN_DMAG())
Arguments
GRN
List produced by simulate_GRN containing GRN structure and statistics.
prior
Prior on causal graphs (default uniform on DMAGs with bkg. info.)
Value
A numeric matrix of posterior probabilities for each possible causal
relationship between the expression traits.
Examples
1
2
GRN <- simulate_GRN(10, 10, 100, 0.1)
derive_BGe_posterior_probabilities(GRN)
igbucur/BFCS documentation built on Oct. 20, 2020, 7:39 a.m.
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Description Usage Arguments Value Examples
Description
Compute the posterior probabilities of L_k -> T_i -> T_j for a simulated GRN using bfcs::compute_BGe_score_vectorized.
Usage
1 | derive_BGe_posterior_probabilities(GRN, prior = uniform_prior_GRN_DMAG())
|
Arguments
GRN |
List produced by simulate_GRN containing GRN structure and statistics. |
prior |
Prior on causal graphs (default uniform on DMAGs with bkg. info.) |
Value
A numeric matrix of posterior probabilities for each possible causal relationship between the expression traits.
Examples
1 2 | GRN <- simulate_GRN(10, 10, 100, 0.1)
derive_BGe_posterior_probabilities(GRN)
|
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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