residuals.index: Extract Model Residuals

In MLID: Multilevel Index of Dissimilarity

Description

For the index of dissimilarity (ID), the residuals are the differences between the share of the Y population and the share of the X population per neighbourhood. For the multilevel index, the residuals are estimated at and partitioned between each level of the model.

Usage

## S3 method for class 'index'
residuals(object, ...)

Arguments

object	an object of class index
...	other arguments

Value

a numeric vector of matrix containing the residuals

See Also

rstandard.index rstudent.index

Examples

data(aggdata)
index <- id(aggdata, vars = c("Bangladeshi", "WhiteBrit"))
# The ID can be derived from the residuals
0.5 * sum(abs(residuals(index)))
# which is the same as
index[1]

# Extract the standardized and look for regions where the share of the
# Bangladeshi population is unusualy high with respect to the White British
# resids <- rstandard(index)
# table(aggdata$RGN[resids > 2.58])

# Residuals for a multilevel index
index <- id(aggdata, vars = c("Bangladeshi", "WhiteBrit"),
levels = c("MSOA","LAD","RGN"))
resids <- residuals(index)
head(resids)
# Again, the ID can be derived from the residuals
0.5 * sum(abs(rowSums(resids)))

# Looking at the residuals, the London effect is different from other regions
sort(tapply(resids[,4], aggdata$RGN, mean))

# At the local authority scale it is Tower Hamlets and Newham
# (both in London) that have the highest share of the Bangladeshi population
# with respect to the White British:
tail(sort(tapply(resids[,3], aggdata$LAD, mean)),5)

MLID documentation built on May 2, 2019, 11:05 a.m.