This function implements the uptake model described in the original Propensity to Cycle Tool paper (Lovelace et al. 2017): https://doi.org/10.5198/jtlu.2016.862

uptake_pct_godutch(
  distance,
  gradient,
  alpha = -3.959 + 2.523,
  d1 = -0.5963 - 0.07626,
  d2 = 1.866,
  d3 = 0.00805,
  h1 = -0.271,
  i1 = 0.009394,
  i2 = -0.05135,
  verbose = FALSE
)

Arguments

distance

Vector distance numeric values of routes in km (switches to km if more than 100).

gradient

Vector gradient numeric values of routes.

alpha

The intercept

d1

Distance term 1

d2

Distance term 2

d3

Distance term 3

h1

Hilliness term 1

i1

Distance-hilliness interaction term 1

i2

Distance-hilliness interaction term 2

verbose

Print messages? FALSE by default.

Details

See uptake_pct_govtarget().

Examples

# https://www.jtlu.org/index.php/jtlu/article/download/862/1381/4359 # Equation 1B: distance = 15 gradient = 2 logit = -3.959 + 2.523 + ((-0.5963 - 0.07626) * distance) + (1.866 * sqrt(distance)) + (0.008050 * distance^2) + (-0.2710 * gradient) + (0.009394 * distance * gradient) + (-0.05135 * sqrt(distance) * gradient) logit
#> [1] -3.144098
# Result: -3.144098 pcycle = exp(logit) / (1 + exp(logit)) # Result: 0.04132445 boot::inv.logit(logit)
#> [1] 0.04132445
uptake_pct_godutch(distance, gradient, alpha = -3.959 + 2.523, d1 = -0.5963 - 0.07626, d2 = 1.866, d3 = 0.008050, h1 = -0.2710, i1 = 0.009394, i2 = -0.05135 )
#> [1] 0.04132445
# these are the default values uptake_pct_godutch(distance, gradient)
#> [1] 0.04132445
l = routes_fast_leeds pcycle_scenario = uptake_pct_godutch(l$length, l$av_incline) plot(l$length, pcycle_scenario)