These are specific codes used in the articles:

• Irving Gómez-Méndez & Emilien Joly (2023). On the consistency of a random forest algorithm in the presence of missing entries, Journal of Nonparametric Statistics.
• Irving Gómez-Méndez & Emilien Joly (2023). Regression with missing data, a comparison study of techniques based on random forests, Journal of Statistical Computation and Simulation.

Examples on the use of these codes as well as updated versions can be found in https://github.com/IrvingGomez/Random_forests_with_missing_values

In Source it can be found "random_forests_with_missing_values.R" which contains the needed functions to construct the random forests with missing values using the approach proposed in "On the consistency of a random forest algorithm in the presence of missing entries".

The file Create_datasets contains the codes to create the training datasets and the testing datasets. While the file Create_RF_and_Predict_RF contains the codes to create the Random Forests using our approach and to predict new observations with missing values accordingly to the procedure described in "Regression with Missing Data, a Comparison Study of Techniques Based on Random Forests"

Finally, the file Calculate_MSE contains the codes to calculate the MSE.

License: All the codes are under the GNU GPL v3 license or any posterior version.

©️ (21-05-2021) Irving Gómez Méndez.