{"title":"利用生存分析建模房地产动态","authors":"Diana Minzat, Mihaela Breaban, H. Luchian","doi":"10.1109/SYNASC.2018.00042","DOIUrl":null,"url":null,"abstract":"This article introduces an adapted version of survival analysis for predicting the period of time a property will stay on market from the listing date to the sale agreement. Survival analysis is a method developed for medical research, in which the dependent variable is the survival time of a patient. Generalizing, the method can be applied in most problems where the dependent variable is time - in our case, the time a property stays on market before selling. Experimental results show that survival analysis brings some advantages when compared to regression analysis on our problem, not only in terms of prediction accuracy: survival curves offer descriptive quantitative views on the influence specific house features have on the variable of interest - the time on market.","PeriodicalId":273805,"journal":{"name":"2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Modeling real estate dynamics using survival analysis\",\"authors\":\"Diana Minzat, Mihaela Breaban, H. Luchian\",\"doi\":\"10.1109/SYNASC.2018.00042\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article introduces an adapted version of survival analysis for predicting the period of time a property will stay on market from the listing date to the sale agreement. Survival analysis is a method developed for medical research, in which the dependent variable is the survival time of a patient. Generalizing, the method can be applied in most problems where the dependent variable is time - in our case, the time a property stays on market before selling. Experimental results show that survival analysis brings some advantages when compared to regression analysis on our problem, not only in terms of prediction accuracy: survival curves offer descriptive quantitative views on the influence specific house features have on the variable of interest - the time on market.\",\"PeriodicalId\":273805,\"journal\":{\"name\":\"2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SYNASC.2018.00042\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SYNASC.2018.00042","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modeling real estate dynamics using survival analysis
This article introduces an adapted version of survival analysis for predicting the period of time a property will stay on market from the listing date to the sale agreement. Survival analysis is a method developed for medical research, in which the dependent variable is the survival time of a patient. Generalizing, the method can be applied in most problems where the dependent variable is time - in our case, the time a property stays on market before selling. Experimental results show that survival analysis brings some advantages when compared to regression analysis on our problem, not only in terms of prediction accuracy: survival curves offer descriptive quantitative views on the influence specific house features have on the variable of interest - the time on market.