Selected article for: "AIC value and parameter estimation"
Author: Liu, Wendi; Tang, Sanyi; Xiao, Yanni
Title: Model Selection and Evaluation Based on Emerging Infectious Disease Data Sets including A/H1N1 and Ebola
  • Document date: 2015_9_15
    • ID: 0j4is0n4_45
    Snippet: In Table 1 . To further confirm the validation of the proposed method, we calculate the AIC value of each model; that is, they are 260, 241, 245, and 231 for models 1 , 2 , 3 , and 4 , respectively. The AIC value for model 4 , Richards model, is the smallest, so the best model is Richards model, which is consistent with the result using Bayes factor. The estimation of parameter values for Richards model is as follows: = ( , , ) = (0.3095, 100.26,.....
    Document: In Table 1 . To further confirm the validation of the proposed method, we calculate the AIC value of each model; that is, they are 260, 241, 245, and 231 for models 1 , 2 , 3 , and 4 , respectively. The AIC value for model 4 , Richards model, is the smallest, so the best model is Richards model, which is consistent with the result using Bayes factor. The estimation of parameter values for Richards model is as follows: = ( , , ) = (0.3095, 100.26, 0.3914) being very close to the real values, shown in the third line of Table 2 .

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