diff --git a/gtsam/inference/Conditional-inst.h b/gtsam/inference/Conditional-inst.h
index 4aa9c5126..9377e8cc4 100644
--- a/gtsam/inference/Conditional-inst.h
+++ b/gtsam/inference/Conditional-inst.h
@@ -57,6 +57,14 @@ double Conditional<FACTOR, DERIVEDCONDITIONAL>::evaluate(
   throw std::runtime_error("Conditional::evaluate is not implemented");
 }
 
+/* ************************************************************************* */
+template <class FACTOR, class DERIVEDCONDITIONAL>
+double Conditional<FACTOR, DERIVEDCONDITIONAL>::logNormalizationConstant()
+    const {
+  throw std::runtime_error(
+      "Conditional::logNormalizationConstant is not implemented");
+}
+
 /* ************************************************************************* */
 template <class FACTOR, class DERIVEDCONDITIONAL>
 double Conditional<FACTOR, DERIVEDCONDITIONAL>::normalizationConstant() const {
@@ -75,8 +83,13 @@ bool Conditional<FACTOR, DERIVEDCONDITIONAL>::CheckInvariants(
   const double logProb = conditional.logProbability(values);
   if (std::abs(prob_or_density - std::exp(logProb)) > 1e-9)
     return false;  // logProb is not consistent with prob_or_density
-  const double expected =
-      conditional.logNormalizationConstant() - conditional.error(values);
+  if (std::abs(conditional.logNormalizationConstant() -
+               std::log(conditional.normalizationConstant())) > 1e-9)
+    return false;  // log normalization constant is not consistent with
+                   // normalization constant
+  const double error = conditional.error(values);
+  if (error < 0.0) return false;  // prob_or_density is negative.
+  const double expected = conditional.logNormalizationConstant() - error;
   if (std::abs(logProb - expected) > 1e-9)
     return false;  // logProb is not consistent with error
   return true;
diff --git a/gtsam/inference/Conditional.h b/gtsam/inference/Conditional.h
index 351d2d4a4..ba7b6897e 100644
--- a/gtsam/inference/Conditional.h
+++ b/gtsam/inference/Conditional.h
@@ -144,10 +144,10 @@ namespace gtsam {
     }
 
     /**
-     * By default, log normalization constant = 0.0.
-     * Override if this depends on the parameters.
+     * All conditional types need to implement a log normalization constant to
+     * make it such that error>=0.
      */
-    virtual double logNormalizationConstant() const { return 0.0; }
+    virtual double logNormalizationConstant() const;
 
     /** Non-virtual, exponentiate logNormalizationConstant. */
     double normalizationConstant() const;
@@ -189,6 +189,8 @@ namespace gtsam {
      *  - evaluate >= 0.0
      *  - evaluate(x) == conditional(x)
      *  - exp(logProbability(x)) == evaluate(x)
+     *  - logNormalizationConstant() = log(normalizationConstant())
+     *  - error >= 0.0
      *  - logProbability(x) == logNormalizationConstant() - error(x)
      *
      * @param conditional The conditional to test, as a reference to the derived type.