Modeling and forecasting carbon dioxide emissions in China using Autoregressive Integrated Moving Average (ARIMA) models

By Thabani Nyoni, Chipo Mutongi. 2019

10 citations recorded by the source corpus.

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1. Akbar Siami Namin
2. Sima Siami‐Namini
3. Omer Berat Sezer

Citations in the corpus

• Forecasting Economics and Financial Time Series: ARIMA vs. LSTM (2018, methodology): “Even though ARIMA models are very pervalent in modeling economical and financial time series [Banerjee 2005; Khashei and Bijari, 2011; Alonso and Garc´ıa-Martos, 2012; Adebiyi et al. 2014], they have some major limitations [Armstrong 2001; Earnest et al. 2005;].”