pair_cor: Correlation matrices for OD data

In LukeCe/spflow: Spatial Econometric Interaction Models

Correlation matrices for OD data

Description

The method computes person correlations for all variables available for the the origins, destinations, and OD-pairs. The OD-pairs information can be either come from a spflow_network_multi or a spflow_models.

Usage

pair_cor(object, ...)

## S4 method for signature 'spflow_network_multi'
pair_cor(
  object,
  id_net_pair = id(object)[["pairs"]][[1]],
  spflow_formula,
  add_lags_x = TRUE,
  add_lags_y = FALSE
)

## S4 method for signature 'spflow_model'
pair_cor(
  object,
  add_fitted = TRUE,
  add_resid = TRUE,
  model,
  exploit_fit = TRUE
)

Arguments

object	A spflow_model-class() or a spflow_network_multi-class()
...	Arguments to be passed to methods
id_net_pair	A character indicating the id of a spflow_network_pair-class()
spflow_formula	A formula specifying how variables should be used (for details see section Formula interface in the help page of spflow())
add_lags_x	A logical, indicating whether spatial lags of the exogenous variables should be included.
add_lags_y	A logical, indicating whether spatial lags of the dependent variables should be included.
add_resid, add_fitted	Logicals, indicating whether the model residuals and fitted value should be added to the correlation matrix
model	A character indicating the model number, that controls different spatial dependence structures should be one of paste0("model_", 1:9). Details are given in the documentation of spflow_control().
exploit_fit	A logical, if TRUE the correlation that is generated as a byproduct of fitting the model is returned. Otherwise it is recreated from the input data, without considering the weights.

Value

A matrix of pairwise correlations between all variables

Author(s)

Lukas Dargel

See Also

spflow_network_multi-class(), spflow_model-class()

Examples

# Used with a spflow_network_multi ...
cor_mat <- pair_cor(multi_net_usa_ge, "ge_ge") # without transformations
cor_image(cor_mat)

cor_mat <- pair_cor( # with transformations and spatial lags
  multi_net_usa_ge,
  "ge_ge",
  y9 ~ . + P_(log(DISTANCE + 1) + .),
  add_lags_y = TRUE)
cor_image(cor_mat)

# Used with a model...
gravity_ge <- spflow(
  y1 ~ . + P_(DISTANCE),
  multi_net_usa_ge,
  "ge_ge",
  spflow_control(model = "model_1"))

cor_mat <- pair_cor(gravity_ge)
cor_image(cor_mat)

LukeCe/spflow documentation built on Nov. 11, 2023, 8:20 p.m.