User Guide#
Welcome to the hpiPy User Guide. This guide walks you through creating and evaluating House Price Indices using various methods—from repeat sales to hedonic pricing to machine learning.
Price Index Methods#
Use one of the following methods to build house price indices:
Build house price indices by pairing repeat sales of unchanged properties.
Model house price indices as a function of house features like size, location, and age.
Use an ensemble of decision trees to learn complex, nonlinear price patterns.
Apply a deep learning model to learn complex, nonlinear price patterns.
Evaluation & Comparison#
Once you’ve created your indices, use the following tools to evaluate and compare methods:
Measure how well an index predicts actual property values.
Quantify the smoothness and stability of an index over time.
Track how index values change with new data over time.
Learn how to analyze and visualize index series.
Compare multiple index construction methods side by side.