Date Thesis Awarded
Honors Thesis -- Access Restricted On-Campus Only
Bachelors of Science (BS)
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.
Zheng, Yujing, "Spatial Analysis with Applications on Real Estate Market Price Prediction" (2017). Undergraduate Honors Theses. William & Mary. Paper 1146.
On-Campus Access Only