Fix Monte Carlo docs

docs/make.jl

@@ -12,13 +12,13 @@ makedocs(
 			"2 Run an Existing Model" => "tutorials/tutorial_2.md",
 			"3 Modify an Existing Model" => "tutorials/tutorial_3.md",
 			"4 Create a Model" => "tutorials/tutorial_4.md",
-			"5 Sensitivity Analysis" => "tutorials/tutorial_5.md"
+			"5 Monte Carlo + Sensitivity Analysis" => "tutorials/tutorial_5.md"
 		],
 		"How-to Guides" => Any[
 			"How-to Guides Intro" => "howto/howto_main.md",
 			"1 Construct + Run a Model" => "howto/howto_1.md",
 			"2 Explore Results" => "howto/howto_2.md",
-			"3 Sensitivity Analysis" => "howto/howto_3.md",
+			"3 Monte Carlo + SA" => "howto/howto_3.md",
 			"4 Timesteps, Params, and Vars" => "howto/howto_4.md",
 			"5 Port to v0.5.0" => "howto/howto_5.md",
 			"6 Port to v1.0.0" => "howto/howto_6.md"

docs/src/howto/howto_3.md

@@ -1,10 +1,10 @@
-# How-to Guide 3: Conduct Sensitivity Analysis
+# How-to Guide 3: Conduct Monte Carlo Simulations and Sensitivity Analysis
 
-Mimi includes a host of routines which support running various sensitivity analysis methods on Mimi models. Tutorial 5: Sensitivity Analysis (SA) Support is a good starting point for learning about these methods.  This how-to guide includes more detail and optionality, covering more advanced options such as non-stochastic scenarios and running multiple models, which are not yet included in the tutorial.
+Mimi includes a host of routines which support running Monte Carlo simulations and various sensitivity analysis methods on Mimi models. Tutorial 5: Monte Carlo Simulations and Sensitivity Analysis Support is a good starting point for learning about these methods.  This how-to guide includes more detail and optionality, covering more advanced options such as non-stochastic scenarios and running multiple models, which are not yet included in the tutorial.
 
 ## Overview
 
-Running a sensitivity analysis in Mimi can be broken down into three primary user-facing elements:
+Running Monte Carlo simulations, and proximal sensitivity analysis, in Mimi can be broken down into three primary user-facing elements:
 
 1. The `@defsim` macro, which defines random variables (RVs) which are assigned distributions and associated with model parameters, and override the default (random) sampling method.
 

docs/src/howto/howto_main.md

@@ -6,19 +6,19 @@ If you find a bug in these guides, or have a clarifying question or suggestion,
 
 ## Available How-to Guides
 
-1. [How-to Guide 1: Construct and Run a Model](@ref) 
+[How-to Guide 1: Construct and Run a Model](@ref) 
 
 
-2. [How-to Guide 2: View and Explore Model Results](@ref) 
+[How-to Guide 2: View and Explore Model Results](@ref) 
 
 
-3. [How-to Guide 3: Conduct Sensitivity Analysis](@ref)
+[How-to Guide 3: Conduct Monte Carlo Simulations and Sensitivity Analysis](@ref)
 
 
-4. [How-to Guide 4: Work with Timesteps, Parameters, and Variables](@ref)
+[How-to Guide 4: Work with Timesteps, Parameters, and Variables](@ref)
 
 
-5. [How-to Guide 5: Port to Mimi v0.5.0](@ref)
+[How-to Guide 5: Port to Mimi v0.5.0](@ref)
 
 
-6. [How-to Guide 6: Port from (>=) Mimi v0.5.0 to Mimi v1.0.0](@ref)
+[How-to Guide 6: Port from (>=) Mimi v0.5.0 to Mimi v1.0.0](@ref)

docs/src/tutorials/tutorial_5.md

@@ -1,6 +1,6 @@
-# Tutorial 5: Sensitivity Analysis (SA) Support
+# Tutorial 5: Monte Carlo Simulations and Sensitivity Analysis Support
 
-This tutorial walks through the sensitivity analysis (SA) functionality of Mimi, including core routines and examples.  We will start with looking at using the SA routines with the multi-region Mimi model built in the second half of Tutorial 3, which is also available in the Mimi repository at `examples/tutorial/02-multi-region-model`. Then we will show some more advanced features using a real Integrated Assessment model, [MimiDICE2010](https://github.com/anthofflab/MimiDICE2010.jl).
+This tutorial walks through the Monte Carlo simulation and sensitivity analysis (SA) functionality of Mimi, including core routines and examples.  We will start with looking at using the Monte Carlo and SA routines with the multi-region Mimi model built in the second half of Tutorial 3, which is also available in the Mimi repository at `examples/tutorial/02-multi-region-model`. Then we will show some more advanced features using a real Integrated Assessment model, [MimiDICE2010](https://github.com/anthofflab/MimiDICE2010.jl).
 
 Working through the following tutorial will require:
 

docs/src/tutorials/tutorial_main.md

@@ -6,19 +6,19 @@ If you find a bug in these tutorials, or have a clarifying question or suggestio
 
 ## Available Tutorials
 
-1. [Tutorial 1: Install Mimi](@ref) describes how to set up your system by installing julia, Mimi, and the Mimi registry.
+[Tutorial 1: Install Mimi](@ref) describes how to set up your system by installing julia, Mimi, and the Mimi registry.
 
 
-2. [Tutorial 2: Run an Existing Model](@ref) steps through the tasks to download, run, and view the results of a registered model such as [FUND](http://www.fund-model.org).  It should be usable for all users, including first-time users, and is a good place to start when learning to use Mimi.
+[Tutorial 2: Run an Existing Model](@ref) steps through the tasks to download, run, and view the results of a registered model such as [FUND](http://www.fund-model.org).  It should be usable for all users, including first-time users, and is a good place to start when learning to use Mimi.
 
 
-3. [Tutorial 3: Modify an Existing Model](@ref) builds on Tutorial 2, showing how to modify an existing model such as [DICE](https://github.com/anthofflab/mimi-dice-2010.jl).
+[Tutorial 3: Modify an Existing Model](@ref) builds on Tutorial 2, showing how to modify an existing model such as [DICE](https://github.com/anthofflab/mimi-dice-2010.jl).
 
 
-4. [Tutorial 4: Create a Model](@ref) takes a step beyond using registered models, explaining how to create a model from scratch.
+[Tutorial 4: Create a Model](@ref) takes a step beyond using registered models, explaining how to create a model from scratch.
 
 
-5. [Tutorial 5: Sensitivity Analysis (SA) Support](@ref) explores Mimi's Sensitivity Analysis support, using both the simple multi-Region tutorial model and MimiDICE2010 examples.
+[Tutorial 5: Monte Carlo Simulations and Sensitivity Analysis Support](@ref) explores Mimi's Monte Carlo simulation and sensitivity analysis support, using both the simple multi-Region tutorial model and MimiDICE2010 examples.
 
 
 _Additional AERE Workshop Tutorials: The Mimi developement team recently participated in the 2019 Association of Environmental and Resource Economists (AERE) summer conference during the pre-conference workshop on Advances in Integrated Assessment Models. This included both a presentation and a hands-on session demonstrating various use cases for Mimi. The Github repository [here](https://github.com/davidanthoff/teaching-2019-aere-workshop) contains a) all slides from the workshop and b) all the code from the hands on sessions, which may be of interest to Mimi users. Importantly note that the linked code represents as a snapshot of Mimi at the time of the workshop, and **will not** be updated to reflect new changes._