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diff --git a/README.md b/README.md
@@ -17,27 +17,12 @@ the output of a function is less than a threshold,
 * sensitivity problems, i.e. estimating sensitivity indices, 
 for example Sobol' indices.
 
-Most of the reliability problems were adapted from the RPRepo :
+Most of the reliability problems were adapted from the RPRepo:
 
 https://rprepo.readthedocs.io/en/latest/
 
 This module allows you to create a problem, run an algorithm and 
 compare the computed probability with a reference probability: 
-
-```
-problem = otb.RminusSReliability()
-event = problem.getEvent()
-pfReference = problem.getProbability() # exact probability
-# Create the Monte-Carlo algorithm
-algoProb = ot.ProbabilitySimulationAlgorithm(event)
-algoProb.setMaximumOuterSampling(1000)
-algoProb.setMaximumCoefficientOfVariation(0.01)
-algoProb.run()
-resultAlgo = algoProb.getResult()
-pf = resultAlgo.getProbabilityEstimate()
-absoluteError = abs(pf - pfReference)
-```
-
 Moreover, we can loop over all problems and run several methods on these 
 problems.
 
@@ -50,71 +35,15 @@ problems.
 
 ## Installation
 
-To install the module, we can use the "git clone" command:
+To install the module, we can use either pip or conda: 
 
 ```
-git clone https://github.com/mbaudin47/otbenchmark.git
-cd otbenchmark
-python setup.py install
+pip install otbenchmark
 ```
 
-## Getting help
-
-The code has docstrings. Hence, using the "help" statement will help. Another way of getting help is to read the examples, which are presented in the next section.
-
-## Overview of the benchmark problems
-
-[Analysis of the R-S case]: https://github.com/mbaudin47/otbenchmark/blob/master/examples/reliability_problems/Cas-R-S.ipynb
-
-[Benchmark the G-Sobol test function]: https://github.com/mbaudin47/otbenchmark/blob/master/examples/sensitivity_problems/GSobolSensitivity.ipynb
-
-[Reliability factories]: https://github.com/mbaudin47/otbenchmark/blob/master/examples/methodFactory.ipynb
-
-[Benchmark on a given set of problems]: https://github.com/mbaudin47/otbenchmark/blob/master/examples/reliability_benchmark.ipynb
-
-[Benchmark the reliability solvers on the problems]: https://github.com/mbaudin47/otbenchmark/blob/master/examples/reliability_benchmark_table.ipynb
-
-[Check reference probabilities with Monte-Carlo]: https://github.com/mbaudin47/otbenchmark/blob/master/examples/reliability_compute_reference_proba.ipynb
-
-The simplest use cas of the library is in [Analysis of the R-S case], which shows how to use this problem with two variables to estimate its failure probability. In the [Benchmark the G-Sobol test function] problem, we show how to estimate sensitivity indices on the G-Sobol' test function. When using a reliability problem, it is convenient to create a given algorithm, e.g. Subset sampling, based on a given problem: the [Reliability factories] shows how to do this for Monte-Carlo, FORM, SORM, Subset and FORM-importance sampling. 
-
-The library currently has:
-* 26 reliability problems,
-* 11 sensitivity problems.
-
-One of the most useful feature of the library is to perform a benchmark that is, loop over the problems. In [Benchmark on a given set of problems], we run several algorithms on all the problems. The associated statistics are gathered in table, presented in [Benchmark the reliability solvers on the problems]. In [Check reference probabilities with Monte-Carlo], we compare the exact (reference) probability with a Monte-Carlo estimate with a large sample.
-
-[Draw events]: https://github.com/mbaudin47/otbenchmark/blob/master/examples/DrawEvent_demo.ipynb
-[Draw cross cut of functions]: https://github.com/mbaudin47/otbenchmark/blob/master/examples/CrossCutFunction_Demo.ipynb
-[Draw cross cuts of distributions]: https://github.com/mbaudin47/otbenchmark/blob/master/examples/CrossCutDistribution-3D_Demo.ipynb
-[Draw conditional distributions]: https://github.com/mbaudin47/otbenchmark/blob/master/examples/ConditionalDistribution_Demo.ipynb
-
-It is often useful to draw a sensitivity or reliability problem. Since many of these problems have dimensions larger than two, this raises a number of practical issues.
-* Event: [Draw events] shows how to draw an multidimensional event,
-* Function: [Draw cross cut of functions] shows how to draw cross cuts of functions,
-* Distribution: [Draw cross cuts of distributions] shows how to draw cross cuts of distributions and [Draw conditional distributions] plots conditional distributions.
-
-The "DrawEvent" class that the module provides typically plots the following figure for the RP57.
-
-![limit_state_surface_RP57.png](figures/limit_state_surface_RP57.png)
-
-The following figure plots cross-cuts of the limit state function for the RP8.
-
-![cross_cut_function_RP8.png](figures/cross_cut_function_RP8.png)
-
-[Examples]: https://github.com/mbaudin47/otbenchmark/tree/master/examples
-
-[BBRC]: https://github.com/mbaudin47/otbenchmark/blob/master/examples-on-server/BBRC.ipynb
-
-[Convergence of Monte-Carlo to estimate the probability in a reliability problem]: https://github.com/mbaudin47/otbenchmark/blob/master/examples/convergence-reliability-Monte-Carlo.ipynb
-
-The [Convergence of Monte-Carlo to estimate the probability in a reliability problem] example might be interesting for those who want to plot convergence graphics.
-
-![convergence_montecarlo.png](figures/convergence_montecarlo.png)
-
-We provide in [BBRC] an example which shows how to use the "evaluate" function that the module provides to evaluate a function which is available in the remote BBRC server. 
+## Documentation
 
-The [Examples] directory has many other examples: please read the notebooks and see if one of the examples fits your needs.
+The documentation is available here: https://openturns.github.io/otbenchmark/master/
 
 ## TODO-List
 

diff --git a/doc/examples/reliability_problems/README.txt → doc/examples/reliability/README.txt b/doc/examples/reliability_problems/README.txt → doc/examples/reliability/README.txt
diff --git a/...roblems/plot_compute_reference_rp55_pf.py → ...methods/plot_compute_reference_rp55_pf.py b/...roblems/plot_compute_reference_rp55_pf.py → ...methods/plot_compute_reference_rp55_pf.py
diff --git a/...blems/plot_print_reliability_benchmark.py → ...thods/plot_print_reliability_benchmark.py b/...blems/plot_print_reliability_benchmark.py → ...thods/plot_print_reliability_benchmark.py
diff --git a/...ty_problems/plot_reliability_benchmark.py → ...ity/methods/plot_reliability_benchmark.py b/...ty_problems/plot_reliability_benchmark.py → ...ity/methods/plot_reliability_benchmark.py
diff --git a/...blems/plot_reliability_benchmark_table.py → ...thods/plot_reliability_benchmark_table.py b/...blems/plot_reliability_benchmark_table.py → ...thods/plot_reliability_benchmark_table.py
diff --git a/...ot_reliability_compute_reference_proba.py → ...ot_reliability_compute_reference_proba.py b/...ot_reliability_compute_reference_proba.py → ...ot_reliability_compute_reference_proba.py
diff --git a/...ples/reliability_problems/plot_case_rs.py → ...ples/reliability/problems/plot_case_rs.py b/...ples/reliability_problems/plot_case_rs.py → ...ples/reliability/problems/plot_case_rs.py
diff --git a/.../plot_four_branch_serial_system_waarts.py → .../plot_four_branch_serial_system_waarts.py b/.../plot_four_branch_serial_system_waarts.py → .../plot_four_branch_serial_system_waarts.py
diff --git a/...amples/reliability_problems/plot_rp110.py → ...amples/reliability/problems/plot_rp110.py b/...amples/reliability_problems/plot_rp110.py → ...amples/reliability/problems/plot_rp110.py
diff --git a/...amples/reliability_problems/plot_rp111.py → ...amples/reliability/problems/plot_rp111.py b/...amples/reliability_problems/plot_rp111.py → ...amples/reliability/problems/plot_rp111.py
diff --git a/...xamples/reliability_problems/plot_rp22.py → ...xamples/reliability/problems/plot_rp22.py b/...xamples/reliability_problems/plot_rp22.py → ...xamples/reliability/problems/plot_rp22.py
diff --git a/...xamples/reliability_problems/plot_rp24.py → ...xamples/reliability/problems/plot_rp24.py b/...xamples/reliability_problems/plot_rp24.py → ...xamples/reliability/problems/plot_rp24.py
diff --git a/...xamples/reliability_problems/plot_rp25.py → ...xamples/reliability/problems/plot_rp25.py b/...xamples/reliability_problems/plot_rp25.py → ...xamples/reliability/problems/plot_rp25.py
diff --git a/...xamples/reliability_problems/plot_rp28.py → ...xamples/reliability/problems/plot_rp28.py b/...xamples/reliability_problems/plot_rp28.py → ...xamples/reliability/problems/plot_rp28.py
diff --git a/...xamples/reliability_problems/plot_rp31.py → ...xamples/reliability/problems/plot_rp31.py b/...xamples/reliability_problems/plot_rp31.py → ...xamples/reliability/problems/plot_rp31.py
diff --git a/...xamples/reliability_problems/plot_rp33.py → ...xamples/reliability/problems/plot_rp33.py b/...xamples/reliability_problems/plot_rp33.py → ...xamples/reliability/problems/plot_rp33.py
diff --git a/...xamples/reliability_problems/plot_rp35.py → ...xamples/reliability/problems/plot_rp35.py b/...xamples/reliability_problems/plot_rp35.py → ...xamples/reliability/problems/plot_rp35.py
diff --git a/...xamples/reliability_problems/plot_rp53.py → ...xamples/reliability/problems/plot_rp53.py b/...xamples/reliability_problems/plot_rp53.py → ...xamples/reliability/problems/plot_rp53.py
diff --git a/...xamples/reliability_problems/plot_rp55.py → ...xamples/reliability/problems/plot_rp55.py b/...xamples/reliability_problems/plot_rp55.py → ...xamples/reliability/problems/plot_rp55.py
diff --git a/...xamples/reliability_problems/plot_rp57.py → ...xamples/reliability/problems/plot_rp57.py b/...xamples/reliability_problems/plot_rp57.py → ...xamples/reliability/problems/plot_rp57.py
diff --git a/...xamples/reliability_problems/plot_rp75.py → ...xamples/reliability/problems/plot_rp75.py b/...xamples/reliability_problems/plot_rp75.py → ...xamples/reliability/problems/plot_rp75.py
diff --git a/...examples/reliability_problems/plot_rp8.py → ...examples/reliability/problems/plot_rp8.py b/...examples/reliability_problems/plot_rp8.py → ...examples/reliability/problems/plot_rp8.py
diff --git a/...xamples/reliability_problems/plot_rp89.py → ...xamples/reliability/problems/plot_rp89.py b/...xamples/reliability_problems/plot_rp89.py → ...xamples/reliability/problems/plot_rp89.py
diff --git a/doc/examples/sensitivity_problems/README.txt → doc/examples/sensitivity/README.txt b/doc/examples/sensitivity_problems/README.txt → doc/examples/sensitivity/README.txt
diff --git a/...ems/plot_benchmark_sensitivity_methods.py → ...ods/plot_benchmark_sensitivity_methods.py b/...ems/plot_benchmark_sensitivity_methods.py → ...ods/plot_benchmark_sensitivity_methods.py
diff --git a/...ity_problems/plot_convergence_ishigami.py → ...vity/methods/plot_convergence_ishigami.py b/...ity_problems/plot_convergence_ishigami.py → ...vity/methods/plot_convergence_ishigami.py
diff --git a/...nsitivity_problems/plot_print_problems.py → ...ensitivity/methods/plot_print_problems.py b/...nsitivity_problems/plot_print_problems.py → ...ensitivity/methods/plot_print_problems.py
diff --git a/...plot_sensitivity_distribution_ishigami.py → ...plot_sensitivity_distribution_ishigami.py b/...plot_sensitivity_distribution_ishigami.py → ...plot_sensitivity_distribution_ishigami.py
diff --git a/...ity_problems/plot_borehole_sensitivity.py → ...ity/problems/plot_borehole_sensitivity.py b/...ity_problems/plot_borehole_sensitivity.py → ...ity/problems/plot_borehole_sensitivity.py
diff --git a/...ty_problems/plot_borgonovo_sensitivity.py → ...ty/problems/plot_borgonovo_sensitivity.py b/...ty_problems/plot_borgonovo_sensitivity.py → ...ty/problems/plot_borgonovo_sensitivity.py
diff --git a/...ty_problems/plot_dirichlet_sensitivity.py → ...ty/problems/plot_dirichlet_sensitivity.py b/...ty_problems/plot_dirichlet_sensitivity.py → ...ty/problems/plot_dirichlet_sensitivity.py
diff --git a/...tivity_problems/plot_flood_sensitivity.py → ...tivity/problems/plot_flood_sensitivity.py b/...tivity_problems/plot_flood_sensitivity.py → ...tivity/problems/plot_flood_sensitivity.py
diff --git a/...lems/plot_gaussian_product_sensitivity.py → ...lems/plot_gaussian_product_sensitivity.py b/...lems/plot_gaussian_product_sensitivity.py → ...lems/plot_gaussian_product_sensitivity.py
diff --git a/...sensitivity_problems/plot_gaussian_sum.py → ...sensitivity/problems/plot_gaussian_sum.py b/...sensitivity_problems/plot_gaussian_sum.py → ...sensitivity/problems/plot_gaussian_sum.py
diff --git a/...ivity_problems/plot_gsobol_sensitivity.py → ...ivity/problems/plot_gsobol_sensitivity.py b/...ivity_problems/plot_gsobol_sensitivity.py → ...ivity/problems/plot_gsobol_sensitivity.py
diff --git a/...ity_problems/plot_ishigami_sensitivity.py → ...ity/problems/plot_ishigami_sensitivity.py b/...ity_problems/plot_ishigami_sensitivity.py → ...ity/problems/plot_ishigami_sensitivity.py
diff --git a/...ivity_problems/plot_morris_sensitivity.py → ...ivity/problems/plot_morris_sensitivity.py b/...ivity_problems/plot_morris_sensitivity.py → ...ivity/problems/plot_morris_sensitivity.py
diff --git a/...problems/plot_nloscillator_sensitivity.py → ...problems/plot_nloscillator_sensitivity.py b/...problems/plot_nloscillator_sensitivity.py → ...problems/plot_nloscillator_sensitivity.py
diff --git a/...problems/plot_oakleyohagan_sensitivity.py → ...problems/plot_oakleyohagan_sensitivity.py b/...problems/plot_oakleyohagan_sensitivity.py → ...problems/plot_oakleyohagan_sensitivity.py
diff --git a/otbenchmark/_AxialStressedBeamReliability.py b/otbenchmark/_AxialStressedBeamReliability.py
@@ -14,12 +14,6 @@ def __init__(self, threshold=0.0):
         Create a axial stressed beam reliability problem.
 
         The inputs are R, the Yield strength, and F, the traction load.
-        The event is {g(X) < threshold} where
-
-        .. math::
-
-            g(R, F) = R - F/(\pi * 100.0)
-
         We have R ~ LogNormalMuSigma() and F ~ Normal().
 
         Parameters

diff --git a/otbenchmark/_DirichletSensitivity.py b/otbenchmark/_DirichletSensitivity.py
@@ -25,7 +25,7 @@ def __init__(self, alpha=ot.Point([1.0 / 2.0, 1.0 / 3.0, 1.0 / 4.0])):
 
         Parameters
         ----------
-        alpha : ot.Point(p), optional
+        alpha : sequence of float, optional
             The coefficients of the model.
 
         Returns
@@ -100,7 +100,7 @@ def ComputeIndices(alpha):
         return exact
 
     def __init__(self, alpha=ot.Point([1.0 / 2.0, 1.0 / 3.0, 1.0 / 4.0])):
-        """
+        r"""
         Create a Dirichlet sensitivity problem.
 
         The function is defined by the equation:
@@ -111,19 +111,19 @@ def __init__(self, alpha=ot.Point([1.0 / 2.0, 1.0 / 3.0, 1.0 / 4.0])):
         where:
 
         .. math::
-            g_i(x) = alpha_i * d_i(x)
+            g_i(x) = \alpha_i * d_i(x)
 
         for any x in [0, 1], where d_i is the Dirichlet kernel:
 
         .. math::
-            d_i(x) = (1 / sqrt(2i)) * (sin((2i + 1) pi x) / sin(pi x) - 1)
+            d_i(x) = \frac{1}{\sqrt(2i)} \frac{\sin((2i + 1) \pi x}{\sin(\pi x) - 1}
 
         for i=1, 2, ..., p.
 
         By continuity, we set:
 
         .. math::
-            d_i(0) = 1 / sqrt(2i) for i=1, 2, ..., p.
+            d_i(0) = i\frac{1}{\sqrt(2i)} for i=1, 2, ..., p.
 
         The Dirichlet kernel has the properties:
 
@@ -135,7 +135,7 @@ def __init__(self, alpha=ot.Point([1.0 / 2.0, 1.0 / 3.0, 1.0 / 4.0])):
 
         Parameters
         ----------
-        alpha : ot.Point(p)
+        alpha : sequence of float
             The vector of coefficients.
 
         Examples

diff --git a/otbenchmark/_OakleyOHaganSensitivity.py b/otbenchmark/_OakleyOHaganSensitivity.py
@@ -12,15 +12,15 @@ class OakleyOHaganSensitivity(SensitivityBenchmarkProblem):
     """Class to define a Oakley-O'Hagan sensitivity benchmark problem."""
 
     def __init__(self):
-        """
+        r"""
         Create a Oakley-O'Hagan sensitivity problem.
 
         The function is defined by the equation:
 
         .. math::
             g(x) = x'Mx+a1'x + a2' sin(x) + a3'cos(x)
 
-        where x1, ..., x15 ~ N(0, 1).
+        where :math:`x_1, \hdots, x_{15} \tilde N(0, 1)`
 
         The input random variables are independent.
 

diff --git a/otbenchmark/_ReliabilityProblem33.py b/otbenchmark/_ReliabilityProblem33.py
@@ -20,15 +20,16 @@ def __init__(
         """
         Creates a reliability problem RP33.
 
-        The event is {g(X) < threshold} where
+        The limit-state g is defined by:
 
-        g(x1, x2, x3) = min(g1, g2) with
+            g(x1, x2, x3) = min(g1, g2) with
 
-        g1 = -x1 - x2 - x3 + 3 * sqrt(3)
+            g1 = -x1 - x2 - x3 + 3 * sqrt(3)
 
-        g2 = -x3 + 3
+            g2 = -x3 + 3
+
+        We have:
 
-        We have :
             x1 ~ Normal(mu[0], sigma[0])
 
             x2 ~ Normal(mu[1], sigma[1])