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)

## 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)
```