Correction in logprob derivation of discrete distributions

pymc/logprob/binary.py

@@ -99,12 +99,10 @@ def comparison_logprob(op, values, base_rv, operand, **kwargs):
     else:
         raise TypeError(f"Unsupported scalar_op {op.scalar_op}")
 
-    if base_rv.dtype.startswith("int"):
-        logp_point = _logprob_helper(base_rv, operand, **kwargs)
-        if isinstance(op.scalar_op, GT):
-            logprob = pt.switch(condn_exp, pt.logaddexp(logprob, logp_point), logprob)
-        elif isinstance(op.scalar_op, LT):
-            logprob = pt.switch(condn_exp, logprob, pt.logaddexp(logprob, logp_point))
+    if base_rv.dtype.startswith("int") and isinstance(op.scalar_op, LT):
+        logpmf = _logprob_helper(base_rv, operand, **kwargs)
+        logcdf_lt_true = _logcdf_helper(base_rv, operand - 1, **kwargs)
+        logprob = pt.switch(condn_exp, logcdf_lt_true, pt.logaddexp(logprob, logpmf))
 
     if base_rv_op.name:
         logprob.name = f"{base_rv_op}_logprob"

tests/logprob/test_binary.py

@@ -51,12 +51,12 @@ def test_continuous_rv_comparison(comparison_op, exp_logp_true, exp_logp_false):
     [
         (
             pt.lt,
-            st.poisson(2).logcdf,
+            lambda x: st.poisson(2).logcdf(x - 1),
             lambda x: np.logaddexp(st.poisson(2).logsf(x), st.poisson(2).logpmf(x)),
         ),
         (
             pt.gt,
-            lambda x: np.logaddexp(st.poisson(2).logsf(x), st.poisson(2).logpmf(x)),
+            st.poisson(2).logsf,
             st.poisson(2).logcdf,
         ),
     ],