Very minor updates to the documentation for Chatterjee Sensitivity do…

…cumentation
SURGroup · Oct 20, 2022 · b82e53e · b82e53e
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diff --git a/docs/source/sensitivity/chatterjee.rst b/docs/source/sensitivity/chatterjee.rst
@@ -23,7 +23,7 @@ The :class:`.ChatterjeeSensitivity` class is imported using the following comman
 Methods
 """""""
 .. autoclass:: UQpy.sensitivity.ChatterjeeSensitivity
-   :members: run, compute_chatterjee_indices, rank_analog_to_pickfreeze, compute_Sobol_indices
+   :members: run, compute_chatterjee_indices, rank_analog_to_pickfreeze, rank_analog_to_pickfreeze_vec, compute_Sobol_indices
 
 Attributes
 """"""""""

diff --git a/src/UQpy/sensitivity/ChatterjeeSensitivity.py b/src/UQpy/sensitivity/ChatterjeeSensitivity.py
@@ -89,7 +89,9 @@ def run(
         confidence_level: PositiveFloat = 0.95,
     ):
         """
-        Compute the sensitivity indices using the Chatterjee method.
+        Compute the sensitivity indices using the Chatterjee method. Employing the :code:`run` method will initialize
+        :code:`n_samples` simulations using :class:`.RunModel`. To compute sensitivity indices using pre-computed inputs
+        and outputs, use the static methods described below.
 
         :param n_samples: Number of samples used to compute the Chatterjee indices. \
             Default is 1,000.