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Table 2 Model summary

From: Predicting Culex pipiens/restuans population dynamics by interval lagged weather data

  β SE z value p
Daily data
Intercept 22.3142 0.5200 42.9118 < 0.0001
D 0, 0 1.0901 0.0281 38.8183 < 0.0001
D 85, 85 0.6453 0.0216 29.8125 < 0.0001
T 0, 0 0.0441 0.0037 11.8177 < 0.0001
T 12, 1 −0.0751 0.0065 −11.5170 < 0.0001
P 0, 0 0.0044 0.0013 3.4509 0.0006
P 51, 16 0.0990 0.0081 12.2828 < 0.0001
H 0, 0 −0.0131 0.0013 −10.2594 < 0.0001
H 38, 1 0.0453 0.0027 17.0574 < 0.0001
W 119, 86 −0.5238 0.0325 −16.1039 < 0.0001
Weekly data
Intercept −22.4553 1.4451 −15.5389 < 0.0001
D 0, 0 1.1318 0.0820 13.8066 < 0.0001
D 13, 13 0.6034 0.0551 10.9537 < 0.0001
T 0, 0 0.0386 0.0150 2.5816 0.0098
T 1, 1 −0.0612 0.0148 −4.1208 < 0.0001
P 7, 3 0.1036 0.0208 4.9686 < 0.0001
H 4, 1 0.0354 0.0061 5.7550 < 0.0001
W 17, 12 −0.5573 0.0940 −5.9315 < 0.0001
  1. Summary of the regression model after the parameter optimization of the lags (OPT) from the daily and weekly data (trainings data set). For each quantity the regression coefficient β and the standard error of the regression coefficient SE, the test statistic (z value) and the p-value is given. The used environmental quantities were D - daytime length, T - temperature, P - precipitation, H - relative humidity, and W - wind speed. The subscript 0,0 represents the environmental quantity at the time of capture. Two subscripts indicate the beginning and the end of the lagged time period.