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Table 4 Fraction of traffic stations (in percent) for which a predictor variable or interaction term is selected by the model selection procedure

From: Modeling hourly weather-related road traffic variations for different vehicle types in Germany

  Highway Federal road
Predictor variable Mot Car Van Trk Mot Car Van Trk
hour 0 0 0 0 0 0 0 0
dow 0 0 0 0 0 0 0 0
mon 100 100 100 100 100 100 100 100
hour:dow 100 100 100 100 100 100 100 100
holiday 6 54 74 99 1 78 79 91
trend 13 38 12 58 19 23 9 27
break 2 4 11 11 1 6 8 4
break:trend 36 32 79 27 10 44 70 38
break:hour 52 33 70 23 14 46 74 48
temp 95 89 76 8 93 86 38 16
temp 33 0 0 0 55 0 0 1
temp\(^2\) 3 4 1 0 7 0 0 0
temp\(^3\) 7 0 0 0 17 0 0 0
temp\(^4\) 15 0 0 0 14 1 0 0
weekend:temp 59 82 54 5 39 82 29 13
weekend:temp\(^2\) 10 18 30 2 18 11 9 3
weekend:temp\(^3\) 7 3 1 1 23 8 1 0
weekend:temp\(^4\) 23 4 1 0 17 18 1 0
cloud 68 10 1 0 99 45 4 0
cloud 3 0 0 0 3 0 0 0
cloud\(^2\) 9 1 0 0 25 0 0 0
cloud\(^3\) 1 0 0 0 3 0 0 0
cloud\(^4\) 0 0 0 0 1 0 0 0
weekend:cloud 18 5 1 0 9 13 2 0
weekend:cloud\(^2\) 31 3 0 0 50 15 1 0
weekend:cloud\(^3\) 5 1 0 0 10 10 1 0
weekend:cloud\(^4\) 1 0 0 0 2 7 0 0
wind 52 7 4 4 89 15 3 1
wind 1 0 0 0 2 0 0 0
wind\(^2\) 3 0 0 0 10 0 0 0
wind\(^3\) 1 0 0 0 6 0 0 0
wind\(^4\) 0 0 0 0 0 0 0 0
weekend:wind 24 6 4 4 7 9 3 0
weekend:wind\(^2\) 14 1 1 0 27 4 0 0
weekend:wind\(^3\) 9 0 0 0 30 2 0 0
weekend:wind\(^4\) 1 0 0 0 7 0 0 0
precip 40 5 25 0 90 1 2 0
precip 0 0 0 0 0 0 0 0
precip\(^{(1/2)}\) 1 0 0 0 1 0 0 0
precip\(^{(1/3)}\) 5 0 1 0 3 0 0 0
precip\(^{(1/4)}\) 3 0 0 0 9 0 0 0
weekend:precip 0 0 0 0 0 0 0 0
weekend:precip\(^{(1/2)}\) 8 0 8 0 11 0 1 0
weekend:precip\(^{(1/3)}\) 11 1 14 0 23 0 1 0
weekend:precip\(^{(1/4)}\) 9 3 1 0 43 1 0 0
  1. Note that for one station a meteorological variable can be selected multiple times, e.g. with different exponents. Rows with italic font show the fraction of stations for which a specific meteorological variable was selected at least once with any exponent or in an interaction term