Model Selection and Evaluation Based on Emerging Infectious Disease Data Sets including A/H1N1 and Ebola

Liu, Wendi; Tang, Sanyi; Xiao, Yanni

The estimation of 0 based on Logistic model is 3.0234 (95% CI (2.6063, 3.4881)), shown in Table 5 For Sierra Leone, it follows from Table 3 that Bayes factorŝ 21 = 102310 > 100,̂3 1 = 34750 > 100, and̂4 1 = 362940 > 100, which implies that there exists decisive evidence for models 2 , 3 , and 4 compared with model 1 (i.e., Logistic model). Moreover, both 3 <̂4 2 = 3.55 < 10 and 10 <̂4 3 = 10.48 < 30 mean that the evidence for the selection of Richards model is stronger than model 3 and more substantial than model 2 . To further confirm the model selection results, we calculate the AIC values to be 15432, 6251, 7038, and 5400 for models 1 , 2 , 3 , and 4 , respectively. The AIC value for Richards model supports us to choose Richards model, which is the best model for us to fit Sierra Leone data. In Figure 3(d) , the numbers of four models which have been selected in the last 2000 runs are 2, 408, 205, and 1385 for models 1 , 2 , 3 , and 4 , respectively, which further confirm that Richards model is the best model for Sierra Leone data set, as shown in Figure 4(d) .