| age_ldv | R Documentation | 
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
Other age: 
age(),
age_hdv(),
age_moto(),
age_veh()
## Not run: 
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)
## End(Not run)
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