# Bayesian Structural Time Series in BSTS package: implementing mixed model

I have been using BSTS package for quite a while and I have found it pretty effective with respect to ARIMAX models.

I was wondering whether it would be possible to share regression coefficients in the regression part (the equation being: $Y_t = \mu_t + \mathbf{x_t} \boldsymbol{\beta} + S_t + \epsilon_t$, with $\mu_t$ being the level at time $t$, $S_t$ being the seasonal component at time $t$) across different time series.

Furthermore I would like to have also mixed effects so that my new equation would become something like:

$Y_{it} = \mu_t + \mathbf{x_t} \boldsymbol{\beta} + \mathbf{Z_t} \boldsymbol{\eta_i}+ S_t + \epsilon_t$.

Question: Is this achievable through BSTS?

Having read Steven Scott presentation I see he implemented Lasso Variable selection and other stuff which makes it difficult for me to implement it directly in STAN..

$$y_{t, j} = Z^T\alpha_t + \beta^Tx_{t, j} + \epsilon_{t, j}$$