Get the samples from the posterior distribution of the regression coefficient matrix B, together with the posterior mean and quantiles. The regression coefficient matrix B is a matrix where the number of rows is defined by the number of traits that are modeled, and the number of columns is the number of columns of the matrix m$X (the number of explanatory variables after transformation via formula)
getB(m)a model fitted with jtdm_fit
A list containing:
Sample from the posterior distribution of the regression coefficient matrix. It is an array where the first dimension is the number of traits, the second the number of columns in m$X (the number of variables after transformation via formula) and the third the number of MCMC samples.
Posterior mean of the regression coefficient matrix.
97.5% and 0.25% posterior quantiles of the regression coefficient matrix.
data(Y)
data(X)
m = jtdm_fit(Y=Y, X=X, formula=as.formula("~GDD+FDD+forest"), sample = 1000)
# get the inferred regression coefficients
B=getB(m)