Robyn

Robyn

Meta
+
+

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About

MPCPy is a Python package that facilitates the testing and implementation of occupant-integrated model predictive control (MPC) for building systems. The package focuses on the use of data-driven, simplified physical or statistical models to predict building performance and optimize control. Four main modules contain object classes to import data, interact with real or emulated systems, estimate and validate data-driven models, and optimize control input. While MPCPy provides an integration platform, it relies on free, open-source, third-party software packages for model implementation, simulators, parameter estimation algorithms, and optimization solvers. This includes Python packages for scripting and data manipulation as well as other more comprehensive software packages for specific purposes. In particular, modeling and optimization for physical systems currently rely on the Modelica language specification.

About

Robyn is an open source, experimental Marketing Mix Modeling (MMM) package developed by Meta’s Marketing Science team. It’s designed to help advertisers and analysts build rigorous, data-driven models that quantify how different marketing channels contribute to business outcomes (like sales, conversions, or other KPIs) in a privacy-safe, aggregated way. Rather than relying on user-level tracking, Robyn analyzes historical time-series data, combining marketing spend or reach data (ads, promotions, organic efforts, etc.) with outcome metrics, to estimate incremental impact, saturation effects, and carry-over (adstock) dynamics. Under the hood, Robyn blends classical statistical methods with modern machine learning and optimization; it uses ridge regression (to regularize against multicollinearity in many-channel models), time-series decomposition to isolate trend and seasonality, and a multi-objective evolutionary algorithm.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Plants and companies requiring an open-source platform to improve their Model Predictive Control (MPC) in their buildings

Audience

Marketing teams, data scientists, and analysts interested in a solution to measure real incremental impact, attribute performance across channels, and optimize budget allocation in a transparent, privacy-compliant way

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

MPCPy
United States
github.com/lbl-srg/MPCPy

Company Information

Meta
Founded: 2004
United States
facebookexperimental.github.io/Robyn/

Alternatives

Cybernetica CENIT

Cybernetica CENIT

Cybernetica

Alternatives

COLUMBO

COLUMBO

PiControl Solutions
INCA MPC

INCA MPC

Inca Tools
AVEVA APC

AVEVA APC

AVEVA

Categories

Categories

Integrations

Facebook
Facebook Ads
Instagram Ads
Meta Ads
Meta Pixel
Python
Ubuntu

Integrations

Facebook
Facebook Ads
Instagram Ads
Meta Ads
Meta Pixel
Python
Ubuntu
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