bidev: Multiscalar Typology (2 deviations)

In MTA: Multiscalar Territorial Analysis

Multiscalar Typology (2 deviations)

Description

Compute a multiscalar typology according to two relative deviations relative.

Usage

bidev(x, dev1, dev2, breaks = c(25, 50, 100), xid = NULL)

Arguments

x	a sf object including 2 deviations among gdev, tdev and sdev.
dev1	column name of the first relative deviation in x.
dev2	coumn name of the second relative deviation in x.
breaks	Distance to the index 100 (average of the context), in percentage. A vector of three values. Defaut c(25,50,100). 25 to indexes 80 and 125. 50 and 200.
xid	identifier field in x. Default the first column.

Value

a column in x including a bidev column delivering the result of the typology. Values are classified in 13 classes according to their respective position on the two selected deviations and their distance to the average.

bidev typology values :

• ZZ: Near the average for the two selected deviation

• A1: Above the average for dev1 and dev2, distance to the avarage : +

• A2: Above the average for dev1 and dev2, distance to the avarage : ++

• A3: Above the average for dev1 and dev2, distance to the avarage : +++

• B1: Above the average for dev1 and below for dev2, distance to the avarage : +

• B2: Above the average for dev1 and below for dev2, distance to the avarage : ++

• B3: Above the average for dev1 and below for dev2, distance to the avarage : +++

• C1: Below the average for dev1 and dev2, distance to the avarage : +

• C2: Below the average for dev1 and dev2, distance to the avarage : ++

• C3: Below the average for dev1 and dev2, distance to the avarage : +++

• D1: Below the average for dev1 and above for dev2, distance to the avarage : +

• D2: Below the average for dev1 and above for dev2, distance to the avarage : ++

• D3: Below the average for dev1 and above for dev2, distance to the avarage : +++

Examples

# bidev synthesis on general and territorial deviation (income data)
# Load data
library(sf)
com <- st_read(system.file("metroparis.gpkg", package = "MTA"), layer = "com", quiet = TRUE)

# Prerequisite  - Compute 2 deviations
com$gdev <- gdev(x = com, var1 = "INC", var2 = "TH")
com$tdev <- tdev(x = com, var1 = "INC", var2 = "TH", key = "EPT")

# Compute bidev
com$bidev <- bidev(x = com, dev1 = "gdev", dev2 = "tdev")

MTA documentation built on Nov. 2, 2023, 5:06 p.m.