Implement log CDF for Laplace distribution

Author: domenzain

pymc3/distributions/continuous.py

@@ -612,6 +612,20 @@ def logp(self, value):
 
         return -tt.log(2 * b) - abs(value - mu) / b
 
+    def logcdf(self, value):
+        a = self.mu
+        b = self.b
+        y = (value - a) / b
+        return tt.switch(
+            tt.le(value, a),
+            tt.log(0.5) + y,
+            tt.switch(
+                tt.gt(y, 1),
+                tt.log1p(-0.5 * tt.exp(-y)),
+                tt.log(1 - 0.5 * tt.exp(-y))
+            )
+        )
+
 
 class Lognormal(PositiveContinuous):
     R"""

pymc3/tests/test_distributions.py

@@ -456,6 +456,8 @@ def test_fun(value, mu, alpha):
     def test_laplace(self):
         self.pymc3_matches_scipy(Laplace, R, {'mu': R, 'b': Rplus},
                                  lambda value, mu, b: sp.laplace.logpdf(value, mu, b))
+        self.check_logcdf(Laplace, R, {'mu': R, 'b': Rplus},
+                          lambda value, mu, b: sp.laplace.logcdf(value, mu, b))
 
     def test_lognormal(self):
         self.pymc3_matches_scipy(