prepare_data: 'prepare_data' prepare data for the estimation.
In nmm: Nonlinear Multivariate Models

Description Usage Arguments Value Examples

prepare_data prepare data for the estimation.

prepare_data(
  data,
  choice = "",
  dummy = "",
  PeID = "",
  WeID = "",
  type = "",
  mode_spec_var = "",
  avl = TRUE,
  chc = TRUE,
  wc = TRUE,
  wd = TRUE,
  nc = 0,
  weights = NULL,
  weight_paths = FALSE,
  weight_paths_cont = FALSE,
  mode_factors = NULL
)

`data`	`data.frame`
`choice`	Name of variable with modes.
`dummy`	Name of variable indicating, if the mode was chosen.
`PeID`	Name of variable with individual identification numbers.
`WeID`	Name of variable with trip identification.
`type`	Type of data. If "long", then modifications are done.
`mode_spec_var`	Used if format "long", mode specific variables.
`avl`	if `TRUE`, includes dummies for mode availability.
`chc`	if `TRUE`, includes dummies for choice of mode.
`wc`	if `TRUE`, creates weights 1 for continuous equations.
`wd`	if `TRUE`, creates weights 1 for discrete equations.
`nc`	Integer, number of continuous equations.
`weights`	Data matrix with weights, column names have to be $wc_i$(continuous), $wd_i$(discrete).
`weight_paths`	if `TRUE`, weight according to number of trips per person, discrete part.
`weight_paths_cont`	if `TRUE`, weight continuous part.
`mode_factors`	if choice is not factor or numeric, this is important to supply.

data.frame used for modeling.

data("TravelMode", package = "AER")
mode_spec_var <- c("wait", "vcost", "travel", "gcost")
res <- prepare_data(TravelMode, choice="mode", dummy="choice", PeID="individual", WeID="",
type="long", mode_spec_var =mode_spec_var, nc=3)