View source: R/UpdateVariances_function.R
MCMC update of the residual variance.
1 2 3 4 5 6 7 8 9 10 11 | UpdateVariances(
X,
Y,
D,
current_alphas,
current_coefs,
alpha_priorX,
alpha_priorY,
beta_priorX,
beta_priorY
)
|
X |
Vector of the treatment |
Y |
Vector of the outcome. |
D |
Matrix or data frame where the columns correspond to all possible predictors of Y, and the rows correspond to the units. |
current_alphas |
Matrix of inclusion indicators with rows corresponding to exposure and outcome models and columns to covariates. |
current_coefs |
Matrix of coefficients with rows corresponding to exposure and outcome models and columns to intercept, exposure and covariates. |
alpha_priorX |
The value of alpha in the inverse gamma prior for the residual variance of the exposure model. |
alpha_priorY |
The value of alpha in the inverse gamma prior for the residual variance of the outcome model. |
beta_priorX |
The value of beta in the inverse gamma prior for the residual variance of the exposure model. |
beta_priorY |
The value of beta in the inverse gamma prior for the residual variance of the outcome model. |
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