With the release of version 0.3.2, hpiR conforms with forthcoming release of dplyr v1.0.0
This package easily calculates house price indexes by the following methods:
- Repeat Sales
- Hedonic Regression
- Interpretable Random Forest (NEW!)
In addition to creating indexes, hpiR also present a standard framework for comparing the quality of indexes across the following measures:
- Volatility
- Revision
- Accuracy
- In-sample
- Out-of-sample (k-fold)
- Out-of-time (forward prediction)
A test dataset of over 43,000 home sales from the City of Seattle is included.
For just getting started, see the Introduction Vignette from within the package or at this link.
For more information on the Interpretable Random Forest method to creating house price index, see this working paper.