APPLICATION OF ITRANSFORMERS TO PREDICTING PRETERM BIRTH RATE. COMPARISON WITH THE ARIMA MODEL
APPLICATION OF ITRANSFORMERS TO PREDICTING PRETERM BIRTH RATE. COMPARISON WITH THE ARIMA MODEL
Author(s): Marek Karwański, Urszula Grzybowska, Vassilis Kostoglou, Ewa Mierzejewska, Katarzyna SzamotulskaSubject(s): Methodology and research technology, Health and medicine and law
Published by: Szkoła Główna Gospodarstwa Wiejskiego w Warszawie
Keywords: time series forecasting; seasonal ARIMA; iTransformers; preterm birth;
Summary/Abstract: In this paper, we study the differences between forecasts obtained with the classical seasonal ARIMA model and forecasts obtained with the neural network model called iTransformers. The analysis is done on Polish data concerning preterm birth from 2015 to 2020. We compare the results and calculate the effect size to conclude the impact of the obtained differences.
Journal: Metody Ilościowe w Badaniach Ekonomicznych
- Issue Year: XXV/2024
- Issue No: 3
- Page Range: 124-133
- Page Count: 10
- Language: English
