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import pymc3 as mc
import theano.tensor as T
## generate some data
nb = 6
nx = 200
b_true_mean = np.random.normal(size=nb) * 5
b_true_cov = np.random.normal(size=(nb,nb))
# imports
import theano
import theano.tensor as T
from theano.ifelse import ifelse
import pymc3 as mc
# some test data
# note: not actually generated by any sensible model, just for technical testing
ncell = 4
ntim = 10