Open AccessEstimating the Long-Term Epidemiological Trends and Seasonality of Hemorrhagic Fever with Renal Syndrome in China
Author(s) -
Yuhan Xiao,
Yanyan Li,
Yuhong Li,
Chongchong Yu,
Yichun Bai,
Lei Wang,
Yongbin Wang
Publication year - 2021
Publication title -
infection and drug resistance
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.033
H-Index - 39
ISSN - 1178-6973
DOI - 10.2147/idr.s325787
Subject(s) - autoregressive integrated moving average , seasonality , statistics , mean absolute percentage error , mean squared error , mean absolute error , mathematics , term (time) , medicine , demography , econometrics , time series , physics , quantum mechanics , sociology
We aim to examine the adequacy of an innovation state-space modeling framework (called TBATS) in forecasting the long-term epidemic seasonality and trends of hemorrhagic fever with renal syndrome (HFRS).