The effectiveness of a probabilistic principal component analysis model and expectation maximisation algorithm in treating missing daily rainfall data

The reliability and accuracy of a risk assessment of extreme hydro-meteorological events are highly dependent on the quality of the historical rainfall time series data. However, missing data in a time series such as this could result in lower quality data. Therefore, this paper proposes a multiple-...

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Bibliographic Details

Main Authors:	Chuan, Zun Liang, Sayang, Mohd Deni, Fam, Soo-Fen, Noriszura, Ismail
Format:	Article
Language:	en en
Published:	Korean Meteorological Society and Springer Nature 2020
Subjects:	GE Environmental Sciences
Online Access:	http://umpir.ump.edu.my/id/eprint/30291/1/The%20Effectiveness%20of%20a%20Probabilistic%20Principal%20Component%20Analysis%20Model%20and%20Expectation%20Maximisation%20Algorithm%20in%20Treating%20Missing%20Daily%20Rainfall%20Data.pdf http://umpir.ump.edu.my/id/eprint/30291/7/The%20Effectiveness%20of%20a%20Probabilistic%20Principal%20Component%20Analysis.pdf http://umpir.ump.edu.my/id/eprint/30291/ https://doi.org/10.1007/s13143-019-00135-8
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