Selected article for: "additive model and GAM generalized additive model"

Author: Tao Liu; Jianxiong Hu; Jianpeng Xiao; Guanhao He; Min Kang; Zuhua Rong; Lifeng Lin; Haojie Zhong; Qiong Huang; Aiping Deng; Weilin Zeng; Xiaohua Tan; Siqing Zeng; Zhihua Zhu; Jiansen Li; Dexin Gong; Donghua Wan; Shaowei Chen; Lingchuan Guo; Yan Li; Limei Sun; Wenjia Liang; Tie Song; Jianfeng He; Wenjun Ma
Title: Time-varying transmission dynamics of Novel Coronavirus Pneumonia in China
  • Document date: 2020_1_26
  • ID: 3e2soc6w_6
    Snippet: Because only the daily number of reporting cases were obtained from regions out of Guangdong Province, we estimated the daily number of incidences using a generalized additive model (GAM) (Section 1.2 in Supplementary materials). First, we collected each individual onset date and reporting date in Guangdong province which was treated as a sample of all confirmed cases nationwide. Second, a GAM model was used to establish the relationship between .....
    Document: Because only the daily number of reporting cases were obtained from regions out of Guangdong Province, we estimated the daily number of incidences using a generalized additive model (GAM) (Section 1.2 in Supplementary materials). First, we collected each individual onset date and reporting date in Guangdong province which was treated as a sample of all confirmed cases nationwide. Second, a GAM model was used to establish the relationship between onset date and reporting date, and obtained the lagged probability distribution of daily number of incidences for the number of reporting cases. Third, we used the lagged probability distribution author/funder. All rights reserved. No reuse allowed without permission.

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