dataBoston              package:spatBMS              R Documentation

_C_o_r_r_e_c_t_e_d _B_o_s_t_o_n _H_o_u_s_i_n_g _D_a_t_a

_D_e_s_c_r_i_p_t_i_o_n:

     The boston.c data frame has 506 rows and 20 columns. It contains
     the Harrison and Rubinfeld (1978) data corrected for a few minor
     errors and augmented with the  latitude and longitude of the
     observations. Gilley and Pace also point out that MEDV is
     censored, in that median values at or over USD 50,000 are set to
     USD 50,000.  The original data set without the corrections is also
     included in package 'mlbench' as 'BostonHousing'. In addition the
     following objects are included: a matrix of tract point
     coordinates projected to UTM zone 19 (included as boston.utm), 
     and a sphere of influence neighbours list ('boston.soi') and the
     one using corrected values in the package 'spdep'.

     The data frame 'dataBoston' contains the variables 'CMEDV', 'DIS',
     'RAD' and 'LSTAT' already in logarithms. On top of that squares of
     the regressors 'RM' ('RM#RM') and 'NOX' ('NOX#NOX')  are provided
     to model potential non-linearities in the data. Furthermore,
     WL.boston is a list object containing extracted eigenvectors
     corresponding to five different spatial weight matrices
     ('WL.boston': the 'boston.soi' matrix, two random perturbations of
     the 'boston.soi' matrix and a knn-4 and knn-6 matrix.).  The
     original matrices are contained in the list object
     'weightM.boston'

_U_s_a_g_e:

     data(dataBoston)

_F_o_r_m_a_t:

     A data frame with 506 observations on the following variables.

     '_T_O_W_N' a factor with levels given by town names 

     '_T_O_W_N_N_O' a numeric vector corresponding to 'TOWN'

     '_T_R_A_C_T' a numeric vector of tract ID numbers 

     '_L_O_N' a numeric vector of tract point longitudes in decimal
          degrees 

     '_L_A_T' a numeric vector of tract point latitudes in decimal degrees 

     '_M_E_D_V' a numeric vector of median values of owner-occupied housing
          in USD 1000 

     '_C_M_E_D_V' a numeric vector of corrected median values of
          owner-occupied housing in USD 1000 

     '_C_R_I_M' a numeric vector of per capita crime 

     '_Z_N' a numeric vector of proportions of residential land zoned for
          lots over 25000 sq. ft per town (constant for all Boston
          tracts)

     '_I_N_D_U_S' a numeric vector of proportions of non-retail business
          acres per town (constant for all Boston tracts) 

     '_C_H_A_S' a factor with levels 1 if tract borders Charles River; 0
          otherwise 

     '_N_O_X' a numeric vector of nitric oxides concentration (parts per
          10 million) per town 

     '_R_M' a numeric vector of average numbers of rooms per dwelling 

     '_A_G_E' a numeric vector of proportions of owner-occupied units
          built prior to 1940 

     '_D_I_S' a numeric vector of weighted distances to five Boston
          employment centres 

     '_R_A_D' a numeric vector of an index of accessibility to radial
          highways per town (constant for all Boston tracts) 

     '_T_A_X' a numeric vector full-value property-tax rate per USD 10,000
          per town (constant for all Boston tracts) 

     '_P_T_R_A_T_I_O' a numeric vector of pupil-teacher ratios per town
          (constant for all Boston tracts) 

     '_B' a numeric vector of 1000*(Bk - 0.63)^2 where Bk is the
          proportion of Afro-Americans 

     '_L_S_T_A_T' a numeric vector of percentage values of lower status
          population 

_S_o_u_r_c_e:

     http://lib.stat.cmu.edu/datasets/boston_corrected.txt

_R_e_f_e_r_e_n_c_e_s:

     Harrison, David, and Daniel L. Rubinfeld, Hedonic Housing Prices
     and the Demand for Clean Air, Journal of Environmental Economics
     and Management, Volume 5, (1978), 81-102. Original data. 

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

     Pace, R. Kelley, and O.W. Gilley, Using the Spatial Configuration
     of the Data to Improve Estimation, Journal of the Real Estate
     Finance and Economics, 14 (1997), 333-340.

_E_x_a_m_p_l_e_s:

     data(dataBoston)

