Publisher Correction: The Effectiveness of a Probabilistic Principal Component Analysis Model and Expectation Maximisation Algorithm in Treating Missing Daily Rainfall Data

IF 2.2 4区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES Asia-Pacific Journal of Atmospheric Sciences Pub Date : 2024-03-27 DOI:10.1007/s13143-024-00363-7
Zun Liang Chuan, Sayang Mohd Deni, Soo-Fen Fam, Noriszura Ismail
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出版商更正:概率主成分分析模型和期望最大化算法在处理缺失日降雨量数据中的有效性
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来源期刊
Asia-Pacific Journal of Atmospheric Sciences
Asia-Pacific Journal of Atmospheric Sciences 地学-气象与大气科学
CiteScore
5.50
自引率
4.30%
发文量
34
审稿时长
>12 weeks
期刊介绍: The Asia-Pacific Journal of Atmospheric Sciences (APJAS) is an international journal of the Korean Meteorological Society (KMS), published fully in English. It has started from 2008 by succeeding the KMS'' former journal, the Journal of the Korean Meteorological Society (JKMS), which published a total of 47 volumes as of 2011, in its time-honored tradition since 1965. Since 2008, the APJAS is included in the journal list of Thomson Reuters’ SCIE (Science Citation Index Expanded) and also in SCOPUS, the Elsevier Bibliographic Database, indicating the increased awareness and quality of the journal.
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