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wider uniform priors for second tier rate models

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commit 684941ae755e2dd0a5a24d1c4c4b940b47619eae 1 parent 2804e91
@aflaxman authored
Showing with 3 additions and 3 deletions.
  1. +2 −2 data_model.py
  2. +1 −1  rate_model.py
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4 data_model.py
@@ -175,7 +175,7 @@ def data_model(name, model, data_type, root_area, root_sex, root_year,
print 'WARNING: %d rows of %s data has no quantification of uncertainty.' % (sum(missing), name)
data['standard_error'][missing] = 1.e6
- vars['sigma'] = mc.Uniform('sigma_%s'%name, lower=.0001, upper=.1, value=.01)
+ vars['sigma'] = mc.Uniform('sigma_%s'%name, lower=.0001, upper=10., value=.01)
vars.update(
rate_model.log_normal_model(name, vars['pi'], vars['sigma'], data['value'], data['standard_error'])
)
@@ -203,7 +203,7 @@ def data_model(name, model, data_type, root_area, root_sex, root_year,
vars += rate_model.poisson(name, vars['pi'], data['value'], data['effective_sample_size'])
elif rate_type == 'offset_log_normal':
- vars['sigma'] = mc.Uniform('sigma_%s'%name, lower=.0001, upper=.1, value=.01)
+ vars['sigma'] = mc.Uniform('sigma_%s'%name, lower=.0001, upper=10., value=.01)
vars += rate_model.offset_log_normal(name, vars['pi'], vars['sigma'], data['value'], data['standard_error'])
else:
raise Exception, 'rate_model "%s" not implemented' % rate_type
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2  rate_model.py
@@ -254,7 +254,7 @@ def offset_log_normal(name, pi, sigma, p, s):
assert pl.all(p > 0), 'observed values must be positive'
assert pl.all(s >= 0), 'standard error must be non-negative'
- p_zeta = mc.Uniform('p_zeta_%s'%name, 1.e-9, 10., value=1.e-6)
+ p_zeta = mc.Uniform('p_zeta_%s'%name, 1.e-9, 1.e9, value=1.e-6)
i_inf = pl.isinf(s)
@mc.observed(name='p_obs_%s'%name)
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