This is the main function to perform MCMC sampling for Balance Regression in linear outcomes
1 | BalReg_mcmc(beta0, V0, lambda, v, w1, w2, Y, X, verbose, iter, start)
|
beta0 |
mean of a multivariate normal distribution which is the prior distribution for regression coefficients |
V0 |
diagnol elements of the variance-covariance matrix of a multivariate normal distribution which is the prior distribution for regression coefficients |
lambda, v |
parameters of the inverse gamma distribution which is the prior distribution of model variance |
w1, w2 |
parameter of prior distribution for the balance configuration vector z |
Y |
outcome vector |
X |
compositional matrix |
verbose |
boolean; indicating whether the program will output verbose progress report |
iter |
total number of iteration to run |
start |
starting value of Balance configuration vector z |
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