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Subset Selection Using Frequency Decomposition with Applications

W. M. Tang, K. F. C. Yiu and H. Wong
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W. M. Tang: Department of Applied Mathematics, The Hong Kong Polytechnic University, Hung Hom Kowloon, Hong Kong, P. R. China
K. F. C. Yiu: Department of Applied Mathematics, The Hong Kong Polytechnic University, Hung Hom Kowloon, Hong Kong, P. R. China
H. Wong: Department of Applied Mathematics, The Hong Kong Polytechnic University, Hung Hom Kowloon, Hong Kong, P. R. China

International Journal of Information Technology & Decision Making (IJITDM), 2020, vol. 19, issue 01, 195-220

Abstract: In time series modeling, one problem is to identify a small number of influential factors to explain variations in the variable of interest. With a vast number of possible factors available, suitable features need to be identified to yield multi-factor models with good explanatory power. In this paper, we propose a novel subset selection method which makes use of the properties in the frequency domain environment. The proposed system ensures key patterns in the target variable be sought and suitable factors be selected based on frequency peaks in common. It can perform well even when the number of factors is significantly greater than the sample size. Moreover, a very important feature of the proposed system is the capability of handling factors with different timeframes, which is lacking in existing methods. We demonstrate the system via several examples with dataset from finance, economic, road traffic and air pollution.

Keywords: Subset selection; frequency analysis; big data analytics; multi-factor model (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1142/S0219622019500500

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