The codes for NHANN

Eğrioğlu, E., Fildes, R. A New Bootstrapped Hybrid Artificial Neural Network Approach for Time Series Forecasting. Comput Econ 59, 1355–1383
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Updated 15 Mar 2023

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The codes for "Eğrioğlu, E., Fildes, R. A New Bootstrapped Hybrid Artificial Neural Network Approach for Time Series Forecasting. Comput Econ 59, 1355–1383 (2022)" paper.
Please use following function as a main function [Stats1,Stats2,ONG,B1,B,RMSETEST,MAPETEST,cbest,drcbest]=simprogrammlpARabctestbest2(x,nt)
İnputs:
nt is the length of the test set (test set is taken from the last part of the series as a block structure)
x is the time series
Ouputs:
Stats1: RMSE statistics
Stats2
ONG: The best one step ahead forecasts for the test set
RMSETEST: The RMSE for the test set with the best model parameters
MAPETEST: The MAPE for the test set with the best model parameters
cbest: The best number of hidden layer units
drcbest: The best number of inputs

Cite As

Erol Egrioglu (2026). The codes for NHANN (https://www.mathworks.com/matlabcentral/fileexchange/126350-the-codes-for-nhann), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2022b
Compatible with any release
Platform Compatibility
Windows macOS Linux
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Version Published Release Notes
1.0.0