columb: Reduced version of Columbus OH crime data

In mgcv: Mixed GAM Computation Vehicle with Automatic Smoothness Estimation

Reduced version of Columbus OH crime data

Description

By district crime data from Columbus OH, together with polygons describing district shape. Useful for illustrating use of simple Markov Random Field smoothers.

Usage

data(columb)
data(columb.polys)

Format

columb is a 49 row data frame with the following columns

area

land area of district

home.value

housing value in 1000USD.

income

household income in 1000USD.

crime

residential burglaries and auto thefts per 1000 households.

open.space

measure of open space in district.

district

code identifying district, and matching names(columb.polys).

columb.polys contains the polygons defining the areas in the format described below.

Details

The data frame columb relates to the districts whose boundaries are coded in columb.polys. columb.polys[[i]] is a 2 column matrix, containing the vertices of the polygons defining the boundary of the ith district. columb.polys[[2]] has an artificial hole inserted to illustrate how holes in districts can be spefified. Different polygons defining the boundary of a district are separated by NA rows in columb.polys[[1]], and a polygon enclosed within another is treated as a hole in that region (a hole should never come first). names(columb.polys) matches columb$district (order unimportant).

Source

The data are adapted from the columbus example in the spdep package, where the original source is given as:

Anselin, Luc. 1988. Spatial econometrics: methods and models. Dordrecht: Kluwer Academic, Table 12.1 p. 189.

Examples

## see ?mrf help files

mgcv documentation built on May 29, 2024, 4:34 a.m.