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)



Numeric; numerical vector of vehicles with length equal to lines features of road network


Character; of vehicle assigned to columns of dataframe


Numeric; parameter of survival equation


Numeric; parameter of survival equation


Integer; age of newest vehicles for that category


Integer; age of oldest vehicles for that category


Numeric; multiplication factor. If its length is > 1, it must match the length of x


Logical; when TRUE it is expecting that 'a' and 'b' are numeric vectors with length equal to x


SpatialLinesDataFrame or Spatial Feature of "LINESTRING"


Logical; message with average age and total numer of vehicles


Any vector to be change row.names. For instance, name of regions or streets.


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


{ data(net) PC_E25_1400 <- age_ldv(x = net$ldv, name = "PC_E25_1400") plot(PC_E25_1400) PC_E25_1400 <- age_ldv(x = net$ldv, name = "PC_E25_1400", net = net) plot(PC_E25_1400) }
#> #> Average = 11.17
#> Warning: plotting the first 9 out of 50 attributes; use max.plot = 50 to plot all