Description Usage Arguments Value Author(s) References See Also
View source: R/updateSigSolo.R
This function samples new values for the sigma squared variances, given the current network structure. A univariate distribution is assumed.
1 | updateSigSolo(X, Y, E, Sall, Ball, Sig2, Mphase, alphad2, betad2, v0, gamma0)
|
X |
Input response data. |
Y |
Input target data. |
E |
Changepoints. |
Sall |
Network structure. |
Ball |
Regression coefficients. |
Sig2 |
Current sigma squared. |
Mphase |
Segment position. |
alphad2 |
Gamma prior hyperparameter. |
betad2 |
Gamma prior hyperparameter. |
v0 |
Inverse gamma prior hyperparameter. |
gamma0 |
Inverse gamma prior hyperparameter. |
Returns the new samples sigma squared values.
Sophie Lebre
For more information about the model, see:
Dondelinger et al. (2012), "Non-homogeneous dynamic Bayesian networks with Bayesian regularization for inferring gene regulatory networks with gradually time-varying structure", Machine Learning.
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