Table 4

Regression tree spatial model results.

Variables Tested and Model Type

Year

R2

Most important variables in model


All variables Regression Tree

All

Precip W17, W19

48.24

Temp W35


2004

Precip W29, W28

70.95

Temp W28


2005

Temp W33

55.57

Precip W24, W26


2006

67.22

Temp W35, W27

Precip W19


2007

Temp W17, W22

61.63

Mean elevation


Weather variables only Regression Tree

All

Precip W17, W19

48.24

Temp W35


2004

Precip W28, W29

68.67

Temp W28


2005

Temp W33

56.27

Precip W24, W26


2006

Temp W35, W27

67.99

Precip W19


2007

Temp W17, W22

61.16

Precip W15


Non-weather variables only Regression Tree

All

8.28

Impervious surface, % pre-40's housing, % 50's housing


2004

47.41

Minimum elevation, Mean elevation, impervious surface


2005

32.23

Maximum elevation, impervious surface, Human population


2006

48.83

Maximum elevation, impervious surface, Human population


2007

42.03

Maximum elevation, impervious surface, Human population


The R2 value indicates the ability of random forests to predict mosquito infection in weeks 32 to 34. Also included are the most important variables from the models listed in order of importance. Results are divided according to which variables were included in the models.

Ruiz et al. Parasites & Vectors 2010 3:19   doi:10.1186/1756-3305-3-19

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