Returns a stepped weighting function to be used inside accessibility calculating functions.
This function is generic over any kind of numeric travel cost, such as distance, time and money.
Arguments
- steps
A
numeric
vector or a list ofnumeric
vectors. The travel cost steps, in ascending order. Please do not include travel cost 0 as a step: this is already handled by the function.- weights
A
numeric
vector with same length assteps
or a list ofnumeric
vectors whose lengths are equal to the lengths of the elements of same index insteps
. The values, between 0 and 1, that the function assumes at each step. Please do not include weight 1 as the first value: this is already handled by the function. The function considers the steps' intervals "open on the right", meaning that the function assumes the step value at the actual step, not right after it. Please see the illustrative examples for effects of this assumption on the results.
Value
A function
that takes a generic travel cost vector (numeric
) as
an input and returns a vector of weights (numeric
).
Details
When both steps
and weights
parameters are given list
s, their
content are matched element-wise to define each stepped weighting function
i.e. the first element of
steps
is matched to the first element ofweights
, the second element ofsteps
is matched to the second ofweights
, etc. When using a function created withdecay_stepped()
, the output is named after the combination of steps ("s"
) and weights ("w"
)e.g. given the steps
c(10, 20, 30)
and the weightsc(0.66, 0.33, 0)
, the output will be named"s(10,20,30);w(0.66,0.33,0)"
.
See also
Other decay functions:
decay_binary()
,
decay_exponential()
,
decay_linear()
,
decay_logistic()
,
decay_power()
Examples
if (FALSE) { # identical(tolower(Sys.getenv("NOT_CRAN")), "true")
weighting_function <- decay_stepped(
c(10, 20, 30, 40),
weights = c(0.75, 0.5, 0.25, 0)
)
weighting_function(c(5, 25, 35, 45))
weighting_function <- decay_stepped(
list(c(10, 20, 30, 40), c(10, 20, 30, 40)),
weights = list(c(0.75, 0.5, 0.25, 0), c(0.8, 0.6, 0.4, 0.2))
)
weighting_function(c(5, 25, 35, 45))
# intervals are open on the right, so the values change exactly at each step
weighting_function(c(0, 10, 20, 30, 40))
}