@@ -184,19 +184,16 @@ def print_row(
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class LinearRegression (PyMCModel ):
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- """
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+ r """
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Custom PyMC model for linear regression.
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Defines the PyMC model
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.. math::
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- \\ beta &\sim \mathrm{Normal}(0, 50)
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-
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- \sigma &\sim \mathrm{HalfNormal}(1)
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-
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- \mu &= X * \\ beta
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-
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- y &\sim \mathrm{Normal}(\mu, \sigma)
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+ \beta &\sim \mathrm{Normal}(0, 50) \\
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+ \sigma &\sim \mathrm{HalfNormal}(1) \\
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+ \mu &= X \cdot \beta \\
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+ y &\sim \mathrm{Normal}(\mu, \sigma) \\
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Example
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--------
@@ -230,20 +227,16 @@ def build_model(self, X, y, coords):
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class WeightedSumFitter (PyMCModel ):
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- """
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+ r """
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Used for synthetic control experiments.
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Defines the PyMC model:
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.. math::
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-
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- \sigma &\sim \mathrm{HalfNormal}(1)
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-
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- \\ beta &\sim \mathrm{Dirichlet}(1,...,1)
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-
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- \mu &= X * \\ beta
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-
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- y &\sim \mathrm{Normal}(\mu, \sigma)
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+ \sigma &\sim \mathrm{HalfNormal}(1) \\
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+ \beta &\sim \mathrm{Dirichlet}(1,...,1) \\
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+ \mu &= X \cdot \beta \\
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+ y &\sim \mathrm{Normal}(\mu, \sigma) \\
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Example
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--------
@@ -423,7 +416,7 @@ def fit(self, X, Z, y, t, coords, priors, ppc_sampler=None):
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class PropensityScore (PyMCModel ):
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- """
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+ r """
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Custom PyMC model for inverse propensity score models
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.. note:
@@ -433,14 +426,10 @@ class PropensityScore(PyMCModel):
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Defines the PyMC model
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.. math::
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- \\ beta &\sim \mathrm{Normal}(0, 1)
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-
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- \sigma &\sim \mathrm{HalfNormal}(1)
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-
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- \mu &= X * \\ beta
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-
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- p &= logit^{-1}(mu)
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-
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+ \beta &\sim \mathrm{Normal}(0, 1) \\
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+ \sigma &\sim \mathrm{HalfNormal}(1) \\
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+ \mu &= X \cdot \beta \\
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+ p &= \text{logit}^{-1}(\mu) \\
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t &\sim \mathrm{Bernoulli}(p)
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Example
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