House Price Indexes

Compute house price indexes and series using a variety of different methods and models common through the real estate literature. Evaluate index 'goodness' based on accuracy, volatility and revision statistics. Background on basic model construction for repeat sales models can be found at: Case and Quigley (1991) <> and for hedonic pricing models at: Bourassa et al (2006) . The package author's working paper on the random forest approach to house price indexes can be found at: <>.

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This package intends to simplify and standardize the creation of house price indexes in R. It also provides a framework for judging the 'quality' of a given index by testing for predictive accuracy, volatility and revision. By providing these metrics various index methods (and estimators) can be accurately compared against each other.

While there are a (ever-increasing) variety of methods and models to use in house price index creation, this initial version (0.2.0) focuses on the two most common: repeat sales (transactions) and hedonic price. Base, robust and weighted estimators are provided when appropriate.

The package also includes a dataset of single family and townhome sales from the City of Seattle during 2010-2016 time period.

Please see the vignette for more information on using the package.

Also, please log issues or pull requests on this github page.


You can install hpiR from github with:

Install the released version from CRAN


Development version from GitHub:



This is a basic example which shows you how to solve a common problem:

  # Load prepared data
  # Create an index
  hpi <- rtIndex(trans_df = ex_rtdata,
                 estimator = 'robust',
                 log_dep = TRUE,
                 trim_model = TRUE,
                 smooth = TRUE)


hpiR 0.2.0

Major Changes

This is the initial release, there are no changes

Bug Fixes

This is the initial release, there are no bug fixes

Minor Changes

This is the initial release, there are no changes

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.


0.3.2 by Andy Krause, 2 years ago

Browse source code at

Authors: Andy Krause [aut, cre]

Documentation:   PDF Manual  

GPL-3 license

Imports dplyr, magrittr, lubridate, robustbase, ggplot2, imputeTS, purrr, forecast, gridExtra, MASS, rlang, plyr, zoo, ranger, pdp

Suggests markdown, testthat, covr, knitr

See at CRAN