Date Thesis Awarded
12-2017
Access Type
Honors Thesis -- Access Restricted On-Campus Only
Degree Name
Bachelors of Science (BS)
Department
Mathematics
Advisor
Guannan Wang
Committee Members
Ross Iaci
John Parman
Abstract
An accurate prediction to the housing prices is very important to all the real estate market participants: homeowners, mortgage lenders, land agents, investors, real estate appraisers, and insurers. Regression analysis is the most widely used modeling technique to determine the relativeness and strength of the relationship between the response variable and explanatory variables. In this project, we focus on the comparison of different regression methods, including the ordinary least squares method, penalized least squares, and univariate and bivariate smoothing techniques, for predicting the real estate market.
Recommended Citation
Zheng, Yujing, "Spatial Analysis with Applications on Real Estate Market Price Prediction" (2017). Undergraduate Honors Theses. William & Mary. Paper 1146.
https://scholarworks.wm.edu/honorstheses/1146
