Bayesian modeling of spatio-temporal point patterns in residential property sales

Lucia Paci, Alan E. Gelfand, MarÍa AsuncÍon Beamonte, Pilar Gargallo, Manuel Salvador

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

It is of important economic interest to understand the market for sales of residential properties. Customary analysis focuses on explaining selling price using property and neighborhood characteristics, so-called hedonic models. Here, our interest is in understanding the locations of the sales. The set of such locations forms a space-time point pattern. With interest in comparing different types of property sales, we obtain marked space-time point patterns according to the size of property. We focus on sales in the city of Zaragoza in Spain during a 10 year period. We employ nonhomogeneous Poisson process models as well as log Gaussian Cox process models, fitted within a Bayesian ramework, with investigation of model adequacy and model comparison.
Original languageEnglish
Title of host publicationProceedings of the 48th scientific meeting of the Italian Statistical Society
Pages1-6
Number of pages6
Publication statusPublished - 2016
Event48 scientific meeting of the Italian Statistical Society - Salerno
Duration: 8 Jun 201610 Jun 2016

Conference

Conference48 scientific meeting of the Italian Statistical Society
CitySalerno
Period8/6/1610/6/16

Keywords

  • MCMC
  • log-Gaussian Cox process
  • marked point pattern
  • nearest neighbor Gaussian process
  • nonhomogeneous Poisson process

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