Online ARIMA algorithms for time series prediction

• Main Authors: LIU, Chenghao, HOI, Steven C. H., ZHAO, Peilin, SUN, Jianling
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2016
• Subjects: Artificial intelligence; Computational efficiency; Estimation; Optimization; Time series; Auto-regressive integrated moving average; Full informations; On-line estimation; Online learning algorithms; Online optimization; Statistical properties; Time series forecasting; Time series prediction; Databases and Information Systems; Theory and Algorithms
• Online Access: https://ink.library.smu.edu.sg/sis_research/3619; https://ink.library.smu.edu.sg/context/sis_research/article/4620/viewcontent/12135_55701_1_PB.pdf
• Institution: Singapore Management University

Autoregressive integrated moving average (ARIMA) is one of the most popular linear models for time series forecasting due to its nice statistical properties and great flexibility. However, its parameters are estimated in a batch manner and its noise terms are often assumed to be strictly bounded, wh...