docs: add info about noisy data

docs/examples/emulator/robustgasp/plot_scalargasp.py

@@ -105,3 +105,14 @@ plt.xlabel('x')
 plt.ylabel('emulator-predicted y')
 plt.xlim(testing_input[0], testing_input[-1])
 _ = plt.legend()
+
+
+# %% md
+#
+# Above example shows how to train a GP emulator based on noise-free training data,
+# which is often the case of emulating a deterministic simulator. If you are dealing
+# with noisy training data, you can
+#
+# - set the parameter ``nugget`` to a desired value, or
+# - set ``nugget`` to :math:`0` and ``nugget_est`` to `True`, meaning that ``nugget``
+#   is estimated from the noisy training data.
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