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GWmodel (version 2.4-1)

LondonHP: London house price data set (SpatialPointsDataFrame)

Description

A house price data set with 18 hedonic variables for London in 2001.

Usage

data(LondonHP)

Arguments

Format

A SpatialPointsDataFrame object (proj4string set to "+init=epsg:27700 +datum=OSGB36").

The "data" slot is a data frame with 372 observations on the following 21 variables.

X

a numeric vector, X coordinate

Y

a numeric vector, Y coordinate

PURCHASE

a numeric vector, the purchase price of the property

FLOORSZ

a numeric vector, floor area of the property in square metres

TYPEDETCH

a numeric vector, 1 if the property is detached (i.e. it is a stand-alone house), 0 otherwise

TPSEMIDTCH

a numeric vector, 1 if the property is semi detached, 0 otherwise

TYPETRRD

a numeric vector, 1 if the property is in a terrace of similar houses (commonly referred to as a 'row house' in the USA), 0 otherwise

TYPEBNGLW

a numeric vector, if the property is a bungalow (i.e. it has only one floor), 0 otherwise

TYPEFLAT

a numeric vector, if the property is a flat (or 'apartment' in the USA), 0 otherwise

BLDPWW1

a numeric vector, 1 if the property was built prior to 1914, 0 otherwise

BLDPOSTW

a numeric vector, 1 if the property was built between 1940 and 1959, 0 otherwise

BLD60S

a numeric vector, 1 if the property was built between 1960 and 1969, 0 otherwise

BLD70S

a numeric vector, 1 if the property was built between 1970 and 1979, 0 otherwise

BLD80S

a numeric vector, 1 if the property was built between 1980 and 1989, 0 otherwise

BLD90S

a numeric vector, 1 if the property was built between 1990 and 2000, 0 otherwise

BATH2

a numeric vector, 1 if the property has more than 2 bathrooms, 0 otherwise

GARAGE

a numeric vector,1 if the house has a garage, 0 otherwise

CENTHEAT

a numeric vector, 1 if the house has central heating, 0 otherwise

BEDS2

a numeric vector, 1 if the property has more than 2 bedrooms, 0 otherwise

UNEMPLOY

a numeric vector, the rate of unemployment in the census ward in which the house is located

PROF

a numeric vector, the proportion of the workforce in professional or managerial occupations in the census ward in which the house is located

Author

Binbin Lu binbinlu@whu.edu.cn

References

Fotheringham, A.S., Brunsdon, C., and Charlton, M.E. (2002), Geographically Weighted Regression: The Analysis of Spatially Varying Relationships, Chichester: Wiley.

Lu, B, Charlton, M, Harris, P, Fotheringham, AS (2014) Geographically weighted regression with a non-Euclidean distance metric: a case study using hedonic house price data. International Journal of Geographical Information Science 28(4): 660-681

Examples

Run this code
data(LondonHP)
data(LondonBorough)
ls()
plot(londonborough)
plot(londonhp, add=TRUE)

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