% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/class_spflow_network_meta.R
\name{spflow_network_classes}
\alias{spflow_network_classes}
\title{Overview on spflow network classes}
\description{
The spflow package provides three additional classes to the R environment.
These allow to handle origin-destination flow data efficiently, by exploiting
the relational structure of origin-destination data.

Data on origins and destinations are stored in the
\code{\link[=spflow_network-class]{spflow_network-class()}} and data on the origin-destination pairs are
stored in an \code{\link[=spflow_network_pair-class]{spflow_network_pair-class()}}.

A third object of type \code{\link[=spflow_network_multi-class]{spflow_network_multi-class()}} gathers all information
from the different data sources.
The class can be thought of as a simple relational database which ensures
correct identification of origin-destination pairs with the node level information.
}
\examples{

### An example use case for the spflow network classes and model estimation
# load example data
data("paris10km_municipalities")
data("paris10km_neighborhood")
data("paris10km_commuteflows")

# define the spflow_network...
# ... they are used as origins and destinations
# ... their neighborhood is based on contiguity
paris10km_net <- spflow_network(
  id_net = "paris10km",
  node_neighborhood = paris10km_neighborhood$by_contiguity,
  node_data = sf::st_drop_geometry(paris10km_municipalities),
  node_key_column = "ID_MUN")

# define the spflow_network_pair...
# ... contains pairwise data (flows and distances)
# ... must be linked to an origin and a destination network
paris10km_net_pairs <- spflow_network_pair(
  id_orig_net = "paris10km",
  id_dest_net = "paris10km",
  pair_data = paris10km_commuteflows,
  orig_key_column = "ID_ORIG",
  dest_key_column = "ID_DEST")


# define the spflow_network_pair...
# ... combines information on nodes and pairs
paris10km_multinet <- spflow_network_multi(paris10km_net,paris10km_net_pairs)

clog <- function(x) {
  y <- log(x)
  y - mean(y)
}

# define the model that we use to explain the flows...
# ... D_() contains destination variables
# ... O_() contains origin variables
# ... D_() contains intra-regional variables (when origin == destination)
# ... P_() contains pair variables (distances)
flow_formula <-
  log(COMMUTE_FLOW + 1) ~
  D_(log(NB_COMPANY) + clog(MED_INCOME)) +
  O_(log(POPULATION) + log(NB_COMPANY) + clog(MED_INCOME)) +
  I_(log(NB_COMPANY) + log(POPULATION)) +
  P_(log(DISTANCE + 1))

# define what variables to use in an SDM specification
# ... if not given all will be used
sdm_formula <-
 ~ D_(log(NB_COMPANY) + clog(MED_INCOME))

# define the list of control parameters
estimation_control <- spflow_control(sdm_variables = sdm_formula)

# Estimate the model
spflow(flow_formula, paris10km_multinet, estimation_control = estimation_control)
}
