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https://github.com/google/GeoexperimentsResearch
An open-source implementation of the geo experiment analysis methodology developed at Google. Disclaimer: This is not an official Google product.
https://github.com/google/GeoexperimentsResearch
Last synced: 3 months ago
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An open-source implementation of the geo experiment analysis methodology developed at Google. Disclaimer: This is not an official Google product.
- Host: GitHub
- URL: https://github.com/google/GeoexperimentsResearch
- Owner: google
- License: apache-2.0
- Archived: true
- Created: 2017-03-21T15:31:57.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2019-10-03T18:11:43.000Z (about 5 years ago)
- Last Synced: 2024-05-14T00:14:18.780Z (6 months ago)
- Language: R
- Homepage:
- Size: 1.5 MB
- Stars: 124
- Watchers: 14
- Forks: 54
- Open Issues: 1
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Metadata Files:
- Readme: README.md
- Changelog: ChangeLog
- Contributing: CONTRIBUTING
- License: LICENSE
Awesome Lists containing this project
- awesome-marketing-machine-learning - GeoexperimentsResearch
README
# R package GeoexperimentsResearch version 1.0.3
Copyright (C) 2017 Google, Inc.
License: Apache 2.0## Disclaimer
This is not an official Google product. For research purposes only.
## What is this R package for?
This R package ('GeoexperimentsResearch') is an open-source implementation of the geo
experiment analysis methodology developed at Google [1, 2].This package provides object classes and methods and functions for handling,
verifying, and analyzing data from geo experiments. Version 1.0 implements the
geo experiment methodology presented in [1], also called the geo-based
regression (GBR), and also the follow-up methodology 'time-based regression'
(TBR), introduced in [2].## Documentation
See the vignette and the manual in this package (in the subdirectory inst/doc/
in the source package).## References
[1] Vaver, J. and Koehler, J. (2011)
[Measuring Ad Effectiveness Using Geo Experiments](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/38355.pdf).[2] Kerman, J., Wang, P. and Vaver, J. (2017)
[Estimating Ad Effectiveness Using Geo Experiments in a Time-Based Regression Framework](https://research.google.com/pubs/pub45950.html).