boston: Boston Housing Data

In GSE: Robust Estimation in the Presence of Cellwise and Casewise Contamination and Missing Data

Boston Housing Data

Description

Housing data for 506 census tracts of Boston from the 1970 census. The dataframe boston contains the corrected data by Harrison and Rubinfeld (1979). The data was for a few minor errors and augmented with the latitude and longitude of the observations. The original data can be found in the references below.

Usage

 data(boston) 

Format

The original data are 506 observations on 14 variables, medv being the target variable:

cmedv	corrected median value of owner-occupied homes in USD 1000's
crim	per capita crime rate by town
indus	proportion of non-retail business acres per town
nox	nitric oxides concentration (parts per 10 million)
rm	average number of rooms per dwelling
age	proportion of owner-occupied units built prior to 1940
dis	weighted distances to five Boston employment centres
rad	index of accessibility to radial highways
tax	full-value property-tax rate per USD 10,000
ptratio	pupil-teacher ratio by town
b	1000(B - 0.63)^2 where B is the proportion of blacks by town
lstat	percentage of lower status of the population

Source

The original data have been taken from the UCI Repository Of Machine Learning Databases at

• http://www.ics.uci.edu/~mlearn/MLRepository.html,

the corrected data have been taken from Statlib at

• https://dasl.datadescription.com/ (originally downloaded from lib.stat.cmu.edu/DASL/)

See Statlib and references there for details on the corrections. Both were converted to R format by Friedrich Leisch.

References

Harrison, D. and Rubinfeld, D.L. (1978). Hedonic prices and the demand for clean air. Journal of Environmental Economics and Management, 5, 81–102.

Gilley, O.W., and R. Kelley Pace (1996). On the Harrison and Rubinfeld Data. Journal of Environmental Economics and Management, 31, 403–405. [Provided corrections and examined censoring.]

Newman, D.J. & Hettich, S. & Blake, C.L. & Merz, C.J. (1998). UCI Repository of machine learning databases [http://www.ics.uci.edu/~mlearn/MLRepository.html]. Irvine, CA: University of California, Department of Information and Computer Science.

Pace, R. Kelley, and O.W. Gilley (1997). Using the Spatial Configuration of the Data to Improve Estimation. Journal of the Real Estate Finance and Economics, 14, 333–340. [Added georeferencing and spatial estimation.]

GSE documentation built on Dec. 28, 2022, 1:31 a.m.