The spflow package provides three additional classes to the R environment that allow to handle origin-destination flow data efficiently.

The main idea is to exploit the relational structure of origin-destination data to reduce the memory requirements. Data on origins and destinations are stored in the sp_network_nodes-class() and data on the origin-destination pairs are stored in an sp_network_pair-class().

A third object of type sp_multi_network-class() is then used to store information on the nodes and pairs in an efficient relational storage. It makes sure that all origin-destination pairs can be identified with the nodes at the origin and destination.

## See also

Other spflow network classes: sp_multi_network-class, sp_network_nodes-class, sp_network_pair-class

Other Constructors for spflow network classes: sp_multi_network, sp_network_nodes, sp_network_pair

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

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

# define the sp_network_pair...
# ... combines information on nodes and pairs
paris10km_multi_net <- sp_multi_network(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)
# ... G_() 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)) +
G_(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
flow_control <- spflow_control(sdm_variables = sdm_formula)

# Estimate the model
spflow(flow_formula, paris10km_multi_net, flow_control = flow_control)
#> Error in clog(MED_INCOME): could not find function "clog"