Added references to bibliography for GSI

docs/code/sensitivity/generalised_sobol/README.rst

@@ -5,10 +5,8 @@ These examples serve as a guide for using the GSI sensitivity module. They have
 
 1. **Mechanical oscillator ODE**
 
-    The GSI sensitivity indices are computed for a mechanical oscillator governed by a second-order differential equation [1]_. The model outputs the displacement of the oscillator for a given time period. Unlike the pointwise-in-time Sobol indices, which provide the sensitivity of the model parameters at each point in time, the GSI indices summarise the sensitivities of the model parameters over the entire time period.
+    The GSI sensitivity indices are computed for a mechanical oscillator governed by a second-order differential equation :cite:`GSI`. The model outputs the displacement of the oscillator for a given time period. Unlike the pointwise-in-time Sobol indices, which provide the sensitivity of the model parameters at each point in time, the GSI indices summarise the sensitivities of the model parameters over the entire time period.
 
 2. **Toy example**
 
-    The GSI sensitivity indices are computed for a toy model whose analytical solution is given in [1]_.
-
-.. [1] Gamboa F, Janon A, Klein T, Lagnoux A, others.  Sensitivity analysis for multidimensional and functional outputs. Electronic journal of statistics 2014; 8(1): 575-603.
+    The GSI sensitivity indices are computed for a toy model whose analytical solution is given in :cite:`GSI`.

docs/source/bibliography.bib

@@ -785,3 +785,19 @@ @article{CVM
 URL = {https://doi.org/10.1137/15M1025621},
 eprint = {https://doi.org/10.1137/15M1025621},
 }
+
+
+# Generalised Sobol index
+@article{GSI,
+author = {Fabrice Gamboa and Alexandre Janon and Thierry Klein and Agnès Lagnoux},
+title = {{Sensitivity analysis for multidimensional and functional outputs}},
+volume = {8},
+journal = {Electronic Journal of Statistics},
+number = {1},
+publisher = {Institute of Mathematical Statistics and Bernoulli Society},
+pages = {575 -- 603},
+keywords = {Concentration inequalities, quadratic functionals, Semi-parametric efficient estimation, sensitivity analysis, Sobol indices, temporal output, vector output},
+year = {2014},
+doi = {10.1214/14-EJS895},
+URL = {https://doi.org/10.1214/14-EJS895}
+}

docs/source/sensitivity/generalised_sobol.rst

@@ -1,7 +1,7 @@
 Generalised Sobol indices
 ----------------------------------------
 
-A natural generalization of the Sobol indices (that are classically defined for single-output models) for multi-output models. The generalised Sobol indices are computed using the Pick-and-Freeze approach. (For implementation details, see also [1]_.)
+A natural generalization of the Sobol indices (that are classically defined for single-output models) for multi-output models. The generalised Sobol indices are computed using the Pick-and-Freeze approach. (For implementation details, see also :cite:`GSI`.)
 
 Consider a model :math:`Y=f(X): \mathbb{R}^d \rightarrow \mathbb{R}^k` with :math:`d` inputs :math:`X=\left[ X_{1}, X_{2},…,X_{d} \right]` and :math:`k` outputs :math:`Y=\left[ Y_{1}, Y_{2},…,Y_{k} \right]`.
 
@@ -47,9 +47,6 @@ and
    \Sigma_{N}=\frac{1}{N} \sum_{j=1}^{N} \frac{Y_{j} Y_{j}^{t}+Y_{j}^{\mathbf{i}}\left(Y_{j}^{\mathbf{i}}\right)^{t}}{2}-\left(\frac{1}{N} \sum_{j=1}^{N} \frac{Y_{j}+Y_{j}^{\mathbf{i}}}{2}\right)\left(\frac{1}{N} \sum_{j=1}^{N} \frac{Y_{j}+Y_{j}^{\mathbf{i}}}{2}\right)^{t}
 
 
-.. [1] Gamboa F, Janon A, Klein T, Lagnoux A, others. Sensitivity analysis for multidimensional and functional outputs. Electronic journal of statistics 2014; 8(1): 575-603.(`Link <https://hal.inria.fr/hal-00881112/document>`_)
-
-
 Generalised Sobol Class
 ^^^^^^^^^^^^^^^^^^^^^^^^^^