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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)) |
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# 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 |