GP versus GLS Spatial Index Models to Forecast Single-Family Home Prices

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Mak (Mahmoud) Kaboudan",
  title =        "GP versus GLS Spatial Index Models to Forecast
                 Single-Family Home Prices",
  journal =      "New Mathematics and Natural Computation",
  year =         "2008",
  volume =       "4",
  number =       "2",
  pages =        "143--163",
  email =        "",
  month =        jul,
  keywords =     "genetic algorithms, genetic programming, generalised
                 least squares, hedonic model, spatial index, home
  DOI =          "doi:10.1142/S1793005708001021",
  abstract =     "This paper investigates use of genetic programming
                 regression models to forecast home values.
                 Neighbourhood prices in a city are represented by a
                 quarterly index. Index values are ratios of each local
                 neighborhood to the global city average real price of
                 homes sold. Relative average neighbourhood home
                 attributes, local socioeconomic characteristics,
                 spatial measures, and real mortgage rates explain
                 spatiotemporal variations in the index. To examine
                 efficacy of model estimation, forecasts obtained using
                 genetic programming are compared with those obtained
                 using generalised least squares. Out-of-sample genetic
                 programming predictions of home prices obtained using
                 spatial index models deliver reasonable forecasts of
                 home prices.",

Genetic Programming entries for Mahmoud A Kaboudan