Analyzing the Influencing Factors of Real Estate Prices Based on Multiple Models

This article analyzes the data of gross domestic product, consumer price index, per capita disposable income, total real estate development investment, annual population at the end of each year, national sales area of commercial housing, and national sales of commercial housing from 2008 to 2022. Multiple linear regression, stepwise regression, Lasso regression, and random forest models are established to compare the national average housing sales with other factors. The regression model is analyzed using R language, and the best model is selected by comparing and adjusting the values and significant variables of R2, VIF, RMSE, MSE. On the basis of this model, analyze the relationship between housing prices and each factor, and provide corresponding countermeasures and suggestions.