Added ICDF for the continuous exponential distribution.

Author: gokuld

pymc/distributions/continuous.py

@@ -1363,6 +1363,15 @@ def logcdf(value, mu):
             msg="lam >= 0",
         )
 
+    def icdf(value, mu):
+        res = -mu * pt.log(1 - value)
+        res = check_icdf_value(res, value)
+        return check_icdf_parameters(
+            res,
+            mu >= 0,
+            msg="mu >= 0",
+        )
+
 
 class Laplace(Continuous):
     r"""

tests/distributions/test_continuous.py

@@ -438,6 +438,20 @@ def test_exponential(self):
             {"lam": Rplus},
             lambda value, lam: st.expon.logcdf(value, 0, 1 / lam),
         )
+        check_icdf(
+            pm.Exponential,
+            {"lam": Rplus},
+            lambda q, lam: st.expon.ppf(q, loc=0, scale=1 / lam),
+        )
+        # Custom logp / logcdf / icdf check for invalid parameters
+        invalid_dist = pm.Exponential.dist(lam=-1)
+        with pytensor.config.change_flags(mode=Mode("py")):
+            with pytest.raises(ParameterValueError):
+                logp(invalid_dist, np.array(0.5)).eval()
+            with pytest.raises(ParameterValueError):
+                logcdf(invalid_dist, np.array(0.5)).eval()
+            with pytest.raises(ParameterValueError):
+                icdf(invalid_dist, np.array(0.5)).eval()
 
     def test_laplace(self):
         check_logp(