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$X (the number of explanatory variables after transformation via formula) getB(m) ## Arguments m a model fitted with jtdm_fit ## Value A list containing: Bsamples Sample from the posterior distribution of the regression coefficient matrix. It is an array where the first dimension is the number of traits, the second the number of columns in m$X (the number of variables after transformation via formula) and the third the number of MCMC samples.

Bmean

Posterior mean of the regression coefficient matrix.

Bq975,Bq025

97.5% and 0.25% posterior quantiles of the regression coefficient matrix.

## Examples

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)