Predicting one time series from another (or many others)?

Questions
4

So I tried to do this, using 16 example time series to try to predict another,

with pm.Model() as model:
    
    mu_beta = pm.Normal('mu_beta', mu=0, sd=10)
    sd_beta = pm.HalfNormal('sd_beta', sd=10)
    beta = pm.Normal('beta', mu=mu_beta, sd=sd_beta, shape=(16))
    input_data = pm.math.dot(train[:,1:17].values, beta)
    
    sd_prior = pm.HalfNormal('std_prior', sd=3)

    observed = pm.Normal('observed', mu = input_data, sd = sd_prior, 
                         observed = train['observed'].values)
    
    trace = pm.sample(cores=4)

but sampling is slow, and I inevitably get a chain failure.

What am I doing wrong here?