Logistic Smooth Transition Autoregressive (LSTAR) and Exponential Smooth Transition Autoregressive (ESTAR) Methods in Predicting the Exchange Rate of Farmers in Lampung Province, Indonesia
Journal Title: International Journal of Multidisciplinary Research and Analysis - Year 2024, Vol 7, Issue 07
Abstract
There are many time series forecasting techniques, one of which is Smooth Transition Autoregressive (STAR). STAR is an extension of the autoregressive model for nonlinear time series data. The STAR model consists of the Logistic STAR (LSTAR) model and the Exponential STAR (ESTAR) model. The aim of this research is to compare which model is more suitable for predicting farmer exchange rates in Lampung Province, Indonesia. The results of this research show that the ESTAR model outperforms the LSTAR model based on a smaller AIC.
Authors and Affiliations
Chyntia Taurinna Krisanti, Netti Herawati, Agus Sutrisno, Nusyirwan
Keywords
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- EP ID EP740019
- DOI 10.47191/ijmra/v7-i07-18
- Views 67
- Downloads 0
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