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Spatio-temporal Modeling and Predictions of House Prices in San Jose- [electronic resource]
Spatio-temporal Modeling and Predictions of House Prices in San Jose- [electronic resource]
상세정보
- 자료유형
- 학위논문(국외)
- 자관 청구기호
- 기본표목-개인명
- 표제와 책임표시사항
- Spatio-temporal Modeling and Predictions of House Prices in San Jose - [electronic resource] / Meng, Haoying.
- 발행, 배포, 간사 사항
- 형태사항
- 1 online resource(102 p)
- 일반주기
- Source: Dissertation Abstracts International, Volume: 78-03(E), Section: B.
- 일반주기
- Advisers: Alexander Aue; Prabir Burman.
- 학위논문주기
- Thesis (Ph.D.)--University of California, Davis, 2016.
- 요약 등 주기
- 요약House prices are of interest to the general public and government agencies for many reasons. The complexity and practicality of house price modeling have attracted many researchers. In this dissertation, attempts are made to explore the dependence structure in time and space among houses using over 130 thousand house price observations in San Jose from 1991 to 2012. Innovative spline methods are utilized to build a forecasting model incorporating both hedonic, spatial and temporal information. The use of splines greatly reduces the number of variables needed in the model without sacrificing for precision. Moreover, the recession period (2008--2010) was given special care because it behaved differently from the rest of the 22 year time period. The model proposed in this dissertation uses both repeat sales and single sale transactions, and is able to produce an overall price index for the whole region, as well as predictions for individual houses. The final model, which includes an autoregressive spatio-temporal error term, is shown to have better predictive abilities than other competing methods in the literature.
- 주제명부출표목-일반주제명
- 부출표목-단체명
- 기본자료저록
- Dissertation Abstracts International. 78-03B(E).
- 기본자료저록
- Dissertation Abstract International
- 전자적 위치 및 접속
- 원문정보보기
- 소장사항
-
20170404 2017
MARC
008170601s2016 us esm 001c eng■001MOKWON01253936
■00520170418115959
■007cr
■020 ▼a9781369311204
■035 ▼a(MiAaPQ)AAI10182805
■040 ▼aMiAaPQ▼cMiAaPQ
■090 ▼a전자도서(박사논문)
■1001 ▼aMeng, Haoying.
■24510▼aSpatio-temporal Modeling and Predictions of House Prices in San Jose▼h[electronic resource]▼cMeng, Haoying.
■260 ▼a[Sl]▼bUniversity of California, Davis▼c2016
■300 ▼a1 online resource(102 p)
■500 ▼aSource: Dissertation Abstracts International, Volume: 78-03(E), Section: B.
■500 ▼aAdvisers: Alexander Aue; Prabir Burman.
■5021 ▼aThesis (Ph.D.)--University of California, Davis, 2016.
■520 ▼aHouse prices are of interest to the general public and government agencies for many reasons. The complexity and practicality of house price modeling have attracted many researchers. In this dissertation, attempts are made to explore the dependence structure in time and space among houses using over 130 thousand house price observations in San Jose from 1991 to 2012. Innovative spline methods are utilized to build a forecasting model incorporating both hedonic, spatial and temporal information. The use of splines greatly reduces the number of variables needed in the model without sacrificing for precision. Moreover, the recession period (2008--2010) was given special care because it behaved differently from the rest of the 22 year time period. The model proposed in this dissertation uses both repeat sales and single sale transactions, and is able to produce an overall price index for the whole region, as well as predictions for individual houses. The final model, which includes an autoregressive spatio-temporal error term, is shown to have better predictive abilities than other competing methods in the literature.
■590 ▼aSchool code: 0029.
■650 4▼aStatistics
■690 ▼a0463
■71020▼aUniversity of California, Davis▼bStatistics.
■7730 ▼tDissertation Abstracts International▼g78-03B(E).
■773 ▼tDissertation Abstract International
■790 ▼a0029
■791 ▼aPh.D.
■792 ▼a2016
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T14489673▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
■980 ▼a20170404▼f2017
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