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

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@Article{Kaboudan:2008:NMNC,

• 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 = "mak_kaboudan@redlands.edu",
• month = jul,
• keywords = "genetic algorithms, genetic programming, generalised least squares, hedonic model, spatial index, home prices",
• 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

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