Added doctests where practical

Project.toml

@@ -14,7 +14,8 @@ julia = "1.7"
 
 [extras]
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
+Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["Test", "DataFrames"]
+test = ["Test", "Documenter", "DataFrames"]

docs/src/release_notes.md

@@ -11,10 +11,10 @@ learning and doubly robust estimation [39](https://github.com/dscolby/CausalELM.
 *   Removed the estimate_causal_effect! call in the model constructor docstrings [#35](https://github.com/dscolby/CausalELM.jl/issues/35)
 *   Standardized and improved docstrings [#44](https://github.com/dscolby/CausalELM.jl/issues/44)
 *   Counterfactual consistency now simulates outcomes that violate the counterfactual consistency assumption rather than 
-binning of treatments and now works with discrete or continuous treatments [#33](https://github.com/dscolby/CausalELM.jl/issues/33)
+binning of treatments and works with discrete or continuous treatments [#33](https://github.com/dscolby/CausalELM.jl/issues/33)
 ### Fixed
 *   Clipped probabilities between 0 and 1 for estimators that use predictions of binary variables [#36](https://github.com/dscolby/CausalELM.jl/issues/36)
-*   Fixed sample splitting and corss fitting procedure for doubly robust estimation [#42](https://github.com/dscolby/CausalELM.jl/issues/42)
+*   Fixed sample splitting and cross fitting procedure for doubly robust estimation [#42](https://github.com/dscolby/CausalELM.jl/issues/42)
 *   Addressed numerical instability when finding the ridge penalty by replacing the previous ridge formula with 
 generalized cross validation [#43](https://github.com/dscolby/CausalELM.jl/issues/43)
 *   Uses the correct variable in the ommited predictor test for interrupted time series.