1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
|
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/properties.R
\docType{data}
\name{properties}
\alias{properties}
\title{Dataset of properties in the municipality of Athens (sf)}
\format{
An sf object of 1000 points with the following 6 variables.
\itemize{
\item{id: An unique identifier for each property.}
\item{size : The size of the property (unit: square meters)}
\item{price : The asking price (unit: euros) }
\item{prpsqm : The asking price per squre meter (unit: euroes/square meter).}
\item{age : Age of property in 2017 (unit: years).}
\item{dist_metro: The distance to closest train/metro station (unit: meters).}
}
}
\usage{
properties
}
\description{
A dataset of apartments in the municipality of Athens for 2017. Point location of the properties is given together with their main characteristics and the distance to the closest metro/train station.
}
\examples{
if (requireNamespace("sf", quietly = TRUE)) {
if (requireNamespace("spdep", quietly = TRUE)) {
library(sf)
library(spdep)
data(properties)
summary(properties$prpsqm)
pr.nb.800 <- dnearneigh(properties, 0, 800)
pr.listw <- nb2listw(pr.nb.800)
moran.test(properties$prpsqm, pr.listw)
moran.plot(properties$prpsqm, pr.listw, xlab = "Price/m^2", ylab = "Lagged")
}
}
}
\seealso{
depmunic
}
\keyword{data}
\keyword{datasets}
\keyword{hierarchical}
\keyword{sf}
\keyword{spatial}
|
