MTA (version 0.1.2)

gdev: General Deviation

Description

This function computes the deviation between regional ratios and a ratio of reference. Each elementary unit's value will be compared to a global value.

Usage

gdev(x, var1, var2, type = "rel", ref = NULL)

Arguments

x

a data frame.

var1

name of the numerator variable in x.

var2

name of the denominator variable in x.

type

type of deviation; "rel" for relative deviation, "abs" for absolute deviation (see Details).

ref

ratio of reference; if NULL, the ratio of reference is the one of the whole study area (sum(var1) / sum(var2)).

Value

A vector is returned.

Details

The relative global deviation is the ratio between var1/var2 and ref (100 * (var1 / var2) / ref). Values greater than 100 indicate that the unit ratio is greater than the ratio of reference. Values lower than 100 indicate that the unit ratio is lower than the ratio of reference. The absolute global deviation is the amount of numerator that could be moved to obtain the ratio of reference on all units.

Examples

# NOT RUN {
# load data
data("GrandParisMetropole")
# compute absolute global deviation
com$gdevabs <- gdev(x = com, var1 = "INC", var2 = "TH", type = "abs")
# compute relative global deviation
com$gdevrel <- gdev(x = com, var1 = "INC", var2 = "TH", type = "rel")

# Deviations maps
if(require('cartography')){
  library(sp)
  # set graphical parameters
  par(mar = c(0,0,1.2,0))
  # set breaks
  bks <- c(min(com$gdevrel),50,75,100,125,150,max(com$gdevrel))
  cols <- carto.pal(pal1 = "blue.pal", n1 = 3,
                    pal2 = "wine.pal", n2 = 3)
  # plot a choropleth map of the relative global deviation
  choroLayer(spdf = com.spdf, df = com, var = "gdevrel",
             legend.pos = "topleft",
             legend.title.txt = "Relative Deviation",
             breaks = bks, border = NA,
             col = cols)
  # add symbols proportional to the absolute general deviation
  com$sign <- ifelse(test = com$gdevabs<0, yes = "negative", no = "positive")
  propSymbolsTypoLayer(spdf = com.spdf, df = com, var = "gdevabs",var2 = "sign",
                       legend.var.pos = "left",legend.values.rnd = -2, 
                       legend.var2.values.order = c("positive", "negative"),
                       legend.var.title.txt = "Absolute Deviation",
                       col = c("#ff000050","#0000ff50"),legend.var2.pos = "n",
                       legend.var.style = "e", inches = 0.2)
  # add EPT boundaries
  plot(ept.spdf, add=TRUE)
  # add a layout
  layoutLayer(title = "General Deviation (reference: Grand Paris Metropole)",
              sources = "GEOFLA<U+00AE> 2015 v2.1, Apur, impots.gouv.fr", 
              north = TRUE,
              author = "MTA")
}
# }