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Table 2 Predictive performance statistics of different models evaluated on the training data for the same time period (months 23−60) to reduce the potential bias

From: Prediction of dengue outbreaks based on disease surveillance, meteorological and socio-economic data

Model Name RMSE SRMSE R-sq.(adj) Deviance Explained Δ AIC
A: Seasonal Naïve 10.22 0.62 0.16 0.16 0
B: Meteorology Optimal 8.83 0.54 0.28 0.32 -492.64
C: Optimal Lag Surveillance Model 7.32 0.45 0.49 0.49 -2420.39
D: Optimal Met and Lag Surveillance Model 6.30 0.39 0.62 0.64 -2725.62
E: Optimal Representation Model 6.12 0.37 0.64 0.66 -2718.90
F: Social-economic data Included 6.10 0.37 0.64 0.73 -2713.86
  1. The performance is measured on different metrics. The best model should have the lowest errors (RMSE, SRMSE) and have the best fit (measured in R-sq.(adj).), high deviance and low Δ AIC