Author: Xiandeng Jiang; Le Chang; Yanlin Shi
Title: How does the outbreak of 2019-nCoV spread in mainland China? A retrospective analysis of the dynamic transmission routes Document date: 2020_3_6
ID: 4k1i6y98_8
Snippet: where x i,t is the accumulated confirmed cases in province i on day t (i = 1, . . . , N and t = 1, . . . , T ). T and N define the number of days and number of provinces under consideration, respectively. We then define y t = (y 1,t , . . . , y N,t ) , an N × 1 vector of the growth rate on day t. To investigate a dynamic direct transmission of the growth rate among provinces, we propose a time-varying coefficient sparse VAR model, namely the tvS.....
Document: where x i,t is the accumulated confirmed cases in province i on day t (i = 1, . . . , N and t = 1, . . . , T ). T and N define the number of days and number of provinces under consideration, respectively. We then define y t = (y 1,t , . . . , y N,t ) , an N × 1 vector of the growth rate on day t. To investigate a dynamic direct transmission of the growth rate among provinces, we propose a time-varying coefficient sparse VAR model, namely the tvSVAR model, which assumes that Granger causality coefficients are functions of time, such that:
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