age_ldv
returns amount of vehicles at each age
age_ldv( x, name = "age", a = 1.698, b = -0.2, agemin = 1, agemax = 50, k = 1, bystreet = F, net, verbose = FALSE, namerows, time )
x | Numeric; numerical vector of vehicles with length equal to lines features of road network |
---|---|
name | Character; of vehicle assigned to columns of dataframe |
a | Numeric; parameter of survival equation |
b | Numeric; parameter of survival equation |
agemin | Integer; age of newest vehicles for that category |
agemax | Integer; age of oldest vehicles for that category |
k | Numeric; multiplication factor. If its length is > 1, it must match the length of x |
bystreet | Logical; when TRUE it is expecting that 'a' and 'b' are numeric vectors with length equal to x |
net | SpatialLinesDataFrame or Spatial Feature of "LINESTRING" |
verbose | Logical; message with average age and total numer of vehicles |
namerows | Any vector to be change row.names. For instance, name of regions or streets. |
time | Character to be the time units as denominator, eg "1/h" |
dataframe of age distrubution of vehicles
The functions age* produce distribution of the circulating fleet by age of use. The order of using these functions is:
1. If you know the distribution of the vehicles by age of use , use: my_age
2. If you know the sales of vehicles, or the registry of new vehicles,
use age
to apply a survival function.
3. If you know the theoretical shape of the circulating fleet and you can use
age_ldv
, age_hdv
or age_moto
. For instance,
you dont know the sales or registry of vehicles, but somehow you know
the shape of this curve.
4. You can use/merge/transform/adapt any of these functions.
It consists in a Gompertz equation with default parameters from 1 national emissions inventory for green housegases in Brazil, MCT 2006