@@ -184,19 +184,16 @@ def print_row(
184184
185185
186186class LinearRegression (PyMCModel ):
187- """
187+ r """
188188 Custom PyMC model for linear regression.
189189
190190 Defines the PyMC model
191191
192192 .. math::
193- \\ beta &\sim \mathrm{Normal}(0, 50)
194-
195- \sigma &\sim \mathrm{HalfNormal}(1)
196-
197- \mu &= X * \\ beta
198-
199- y &\sim \mathrm{Normal}(\mu, \sigma)
193+ \beta &\sim \mathrm{Normal}(0, 50) \\
194+ \sigma &\sim \mathrm{HalfNormal}(1) \\
195+ \mu &= X \cdot \beta \\
196+ y &\sim \mathrm{Normal}(\mu, \sigma) \\
200197
201198 Example
202199 --------
@@ -230,20 +227,16 @@ def build_model(self, X, y, coords):
230227
231228
232229class WeightedSumFitter (PyMCModel ):
233- """
230+ r """
234231 Used for synthetic control experiments.
235232
236233 Defines the PyMC model:
237234
238235 .. math::
239-
240- \sigma &\sim \mathrm{HalfNormal}(1)
241-
242- \\ beta &\sim \mathrm{Dirichlet}(1,...,1)
243-
244- \mu &= X * \\ beta
245-
246- y &\sim \mathrm{Normal}(\mu, \sigma)
236+ \sigma &\sim \mathrm{HalfNormal}(1) \\
237+ \beta &\sim \mathrm{Dirichlet}(1,...,1) \\
238+ \mu &= X \cdot \beta \\
239+ y &\sim \mathrm{Normal}(\mu, \sigma) \\
247240
248241 Example
249242 --------
@@ -423,7 +416,7 @@ def fit(self, X, Z, y, t, coords, priors, ppc_sampler=None):
423416
424417
425418class PropensityScore (PyMCModel ):
426- """
419+ r """
427420 Custom PyMC model for inverse propensity score models
428421
429422 .. note:
@@ -433,14 +426,10 @@ class PropensityScore(PyMCModel):
433426 Defines the PyMC model
434427
435428 .. math::
436- \\ beta &\sim \mathrm{Normal}(0, 1)
437-
438- \sigma &\sim \mathrm{HalfNormal}(1)
439-
440- \mu &= X * \\ beta
441-
442- p &= logit^{-1}(mu)
443-
429+ \beta &\sim \mathrm{Normal}(0, 1) \\
430+ \sigma &\sim \mathrm{HalfNormal}(1) \\
431+ \mu &= X \cdot \beta \\
432+ p &= \text{logit}^{-1}(\mu) \\
444433 t &\sim \mathrm{Bernoulli}(p)
445434
446435 Example
0 commit comments