Abstract
This study compares the performance of various spatial prediction models which consider spatial dependence among the real estate data in spatial econometrics, spatial statistics, and semiparametric statistics. Thus far, surprisingly few researches have been conducted from this perspective. This study employs the dataset of apartment rent in the Tokyo 23 wards for empirical comparison. This study in particular focuses on a geoadditive model which considers both spatial dependence and nonlinearity of a hedonic function, and suggests the predictive performance of this method superior to those of the traditional methods like kriging or EM type algorithm.
| Original language | English |
|---|---|
| Title of host publication | Procedia - Social and Behavioral Sciences |
| Pages | 120-129 |
| Number of pages | 10 |
| Volume | 21 |
| DOIs | |
| Publication status | Published - 2011 |
| Event | International Conference on Spatial Thinking and Geographic Information Sciences 2011, STGIS 2011 - Tokyo, Japan Duration: 2011 Sep 14 → 2011 Sep 16 |
Other
| Other | International Conference on Spatial Thinking and Geographic Information Sciences 2011, STGIS 2011 |
|---|---|
| Country | Japan |
| City | Tokyo |
| Period | 11/9/14 → 11/9/16 |
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Keywords
- Apartment rent
- Geoadditive model
- Nonlinearity
- Spatial hedonic model
- Spatial prediction
ASJC Scopus subject areas
- Social Sciences(all)
- Psychology(all)
Cite this
Empirical comparison of the various spatial prediction models : In spatial econometrics, spatial statistics, and semiparametric statistics. / Seya, Hajime; Tsutsumi, Morito; Yoshida, Yasushi; Kawaguchi, Yuichiro.
Procedia - Social and Behavioral Sciences. Vol. 21 2011. p. 120-129.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Empirical comparison of the various spatial prediction models
T2 - In spatial econometrics, spatial statistics, and semiparametric statistics
AU - Seya, Hajime
AU - Tsutsumi, Morito
AU - Yoshida, Yasushi
AU - Kawaguchi, Yuichiro
PY - 2011
Y1 - 2011
N2 - This study compares the performance of various spatial prediction models which consider spatial dependence among the real estate data in spatial econometrics, spatial statistics, and semiparametric statistics. Thus far, surprisingly few researches have been conducted from this perspective. This study employs the dataset of apartment rent in the Tokyo 23 wards for empirical comparison. This study in particular focuses on a geoadditive model which considers both spatial dependence and nonlinearity of a hedonic function, and suggests the predictive performance of this method superior to those of the traditional methods like kriging or EM type algorithm.
AB - This study compares the performance of various spatial prediction models which consider spatial dependence among the real estate data in spatial econometrics, spatial statistics, and semiparametric statistics. Thus far, surprisingly few researches have been conducted from this perspective. This study employs the dataset of apartment rent in the Tokyo 23 wards for empirical comparison. This study in particular focuses on a geoadditive model which considers both spatial dependence and nonlinearity of a hedonic function, and suggests the predictive performance of this method superior to those of the traditional methods like kriging or EM type algorithm.
KW - Apartment rent
KW - Geoadditive model
KW - Nonlinearity
KW - Spatial hedonic model
KW - Spatial prediction
UR - http://www.scopus.com/inward/record.url?scp=82555185699&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=82555185699&partnerID=8YFLogxK
U2 - 10.1016/j.sbspro.2011.07.025
DO - 10.1016/j.sbspro.2011.07.025
M3 - Conference contribution
VL - 21
SP - 120
EP - 129
BT - Procedia - Social and Behavioral Sciences
ER -