City-Scale Bayesian Spatial Modeling for House Pricing
Shirley Ren, Emily B. Fox

Citation
Shirley Ren, Emily B. Fox. "City-Scale Bayesian Spatial Modeling for House Pricing". Talk or presentation, 30, October, 2014; Poster presented at the 2014 TerraSwarm Annual Meeting.

Abstract
In our applications of interest, we are faced with a collection of n time series representing house sale prices from n geographical regions, e.g. census tracts. Our goal is to discover price dynamics shared between these region-specific time series. Through this process, we can infer how the data streams relate to one another as well as harness the shared structure to pool observations from related price dynamics, thereby improving our estimates of the dynamic parameters.

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Citation formats

• HTML

  Shirley Ren, Emily B. Fox. <a
  href="http://www.terraswarm.org/pubs/420.html"><i>City-Scale
  Bayesian Spatial Modeling for House
  Pricing</i></a>, Talk or presentation,  30,
  October, 2014; Poster presented at the <a
  href="http://www.terraswarm.org/conferences/14/annual"
  >2014 TerraSwarm Annual Meeting</a>.

• Plain text

  Shirley Ren, Emily B. Fox. "City-Scale Bayesian Spatial
  Modeling for House Pricing". Talk or presentation,  30,
  October, 2014; Poster presented at the <a
  href="http://www.terraswarm.org/conferences/14/annual"
  >2014 TerraSwarm Annual Meeting</a>.

• BibTeX

  @presentation{RenFox14_CityScaleBayesianSpatialModelingForHousePricing,
      author = {Shirley Ren and Emily B. Fox},
      title = {City-Scale Bayesian Spatial Modeling for House
                Pricing},
      day = {30},
      month = {October},
      year = {2014},
      note = {Poster presented at the <a
                href="http://www.terraswarm.org/conferences/14/annual"
                >2014 TerraSwarm Annual Meeting</a>.},
      abstract = {In our applications of interest, we are faced with
                a collection of n time series representing house
                sale prices from n geographical regions, e.g.
                census tracts. Our goal is to discover price
                dynamics shared between these region-specific time
                series. Through this process, we can infer how the
                data streams relate to one another as well as
                harness the shared structure to pool observations
                from related price dynamics, thereby improving our
                estimates of the dynamic parameters.},
      URL = {http://terraswarm.org/pubs/420.html}
  }
  

Posted by Shirley Ren, Ms. on 1 Nov 2014.
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