gamlss.data (version 5.1-4)

rent: Rent data

Description

A survey was conducted in April 1993 by Infratest Sozialforschung. A random sample of accommodation with new tenancy agreements or increases of rents within the last four years in Munich was selected including: i) single rooms, ii) small apartments, iii) flats, iv) two-family houses. Accommodation subject to price control rents, one family houses and special houses, such as penthouses, were excluded because they are rather different from the rest and are considered a separate market. For the purpose of this study, 1967 observations of the variables listed below were used, i.e. the rent response variable R followed by the explanatory variables found to be appropriate for a regression analysis approach by Fahrmeir et al. (1994, 1995):

Usage

data(rent)

Format

A data frame with 1969 observations on the following 9 variables.

R

: rent response variable, the monthly net rent in DM, i.e. the monthly rent minus calculated or estimated utility cost

Fl

: floor space in square meters

A

: year of construction

Sp

: a variable indicating whether the location is above average, 1, (550 observations) or not, 0, (1419 observations)

Sm

: a variable indicating whether the location is below, 1, average (172 obs.) or not, 0, (1797 obs.)

B

: a factor with levels indicating whether there is a bathroom, 1, (1925 obs.) or not, 0, (44 obs.)

H

: a factor with levels indicating whether there is central heating, 1, (1580 obs.) or not, 0, (389 obs.)

L

: a factor with levels indicating whether the kitchen equipment is above average, 1, (161 obs.) or not, 0, (1808 obs.)

loc

: a factor (combination of Sp and Sm) indicating whether the location is below, 1, average, 2, or above average 3

Details

This set of data were used by Stasinopoulos et al. (2000) to fit a model where both the mean and the dispersion parameter of a Gamma distribution were modelled using the explanatory variables.

References

Fahrmeir L., Gieger C., Mathes H. and Schneeweiss H. (1994) Gutachten zur Erstellung des Mietspiegels fur Munchen 1994, Teil B: Statistiche Analyse der Nettomieten. Hrsg: Landeshaupttstadt Munchen, Sozialreferat-Amt fur Wohnungswesen.

Fahrmeir L., Gieger C., and Klinger, A. (1995) Additive, dynamic and multiplicative regression. In Applied Statistics: Recent Developments, Vandenhoeck and Ruprecht, Gottingen.

Stasinopoulos, D. M., Rigby, R. A. and Fahrmeir, L., (2000), Modelling rental guide data using mean and dispersion additive models, Statistician, 49 , 479-493.

Stasinopoulos D. M. Rigby R.A. (2007) Generalized additive models for location scale and shape (GAMLSS) in R. Journal of Statistical Software, Vol. 23, Issue 7, Dec 2007, http://www.jstatsoft.org/v23/i07.

Examples

# NOT RUN {
data(rent)
attach(rent)
plot(Fl,R)
# }