Reduced version of Columbus OH crime data
By district crime data from Columbus OH, together with polygons describing district shape. Useful for illustrating use of simple Markov Random Field smoothers.
data(columb) data(columb.polys)
columb
is a 49 row data frame with the following columns
land area of district
housing value in 1000USD.
household income in 1000USD.
residential burglaries and auto thefts per 1000 households.
measure of open space in district.
code identifying district, and matching names(columb.polys)
.
columb.polys
contains the polygons defining the areas in the format described below.
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).
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.
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