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Average Ratings 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

No User Reviews. Be the first to provide a review:

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Description

R is a comprehensive environment and programming language tailored for statistical analysis and graphical representation. As a part of the GNU project, it shares similarities with the S language, which was originally designed by John Chambers and his team at Bell Laboratories, now known as Lucent Technologies. Essentially, R serves as an alternative implementation of S, and while there are notable distinctions between the two, a significant amount of S code can be executed in R without modification. This versatile language offers a broad spectrum of statistical methods, including both linear and nonlinear modeling, classical statistical tests, time-series analytics, classification, and clustering, among others, and it boasts a high level of extensibility. The S language is frequently utilized in research focused on statistical methodologies, and R presents an Open Source avenue for engaging in this field. Moreover, one of R's key advantages lies in its capability to generate high-quality publication-ready graphics, facilitating the inclusion of mathematical symbols and formulas as needed, which enhances its usability for researchers and analysts alike. Ultimately, R continues to be a powerful tool for those seeking to explore and visualize data effectively.

Description

Robyn is a cutting-edge, open-source Marketing Mix Modeling (MMM) tool created by Meta’s Marketing Science team for experimental purposes. It aims to assist advertisers and analysts in constructing thorough, data-driven models that assess how various marketing channels affect business results, such as sales and conversions, while ensuring privacy through aggregated data. Instead of depending on tracking individual users, Robyn delves into historical time-series data by integrating marketing expenditure or reach information—encompassing ads, promotions, and organic initiatives—with performance indicators to evaluate incremental impacts, saturation effects, and carry-over dynamics. The package utilizes a combination of classical statistical techniques and contemporary machine learning methods; it employs ridge regression to mitigate multicollinearity in complex models, performs time-series decomposition to differentiate between trends and seasonal patterns, and incorporates a multi-objective evolutionary algorithm for optimization. This innovative approach allows businesses to gain deeper insights into their marketing effectiveness and make more informed decisions based on robust analysis.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Betteromics Yes 
Claude Mythos 5.1 Yes 
Claude Opus 4.5 Yes 
CodeBanana Yes 
CodeFactor Yes 
Decentriq Yes 
DeepSeek-V3 Yes 
DeepSeek-V4 Yes 
GPT-4.1 Yes 
GPT-5.6 Luna Yes 
GPT-6 Luna Yes 
GPT‑6 Cyber Yes 
Gemini 3.8 Flash Yes 
Llama 4 Behemoth Yes 
Mixtral 8x22B Yes 
Muse Spark 1.2 Yes 
Qwen2.5 Yes 
Qwen3 Yes 
Raven Yes 
SWE-2 Flash Yes 

Integrations

Betteromics No 
Claude Mythos 5.1 No 
Claude Opus 4.5 No 
CodeBanana No 
CodeFactor No 
Decentriq No 
DeepSeek-V3 No 
DeepSeek-V4 No 
GPT-4.1 No 
GPT-5.6 Luna No 
GPT-6 Luna No 
GPT‑6 Cyber No 
Gemini 3.8 Flash No 
Llama 4 Behemoth No 
Mixtral 8x22B No 
Muse Spark 1.2 No 
Qwen2.5 No 
Qwen3 No 
Raven No 
SWE-2 Flash No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

The R Foundation

Website

www.r-project.org

Vendor Details

Company Name

Meta

Founded

2004

Country

United States

Website

facebookexperimental.github.io/Robyn/

Product Features

Product Features

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