R

R

The R Foundation
Scilab

Scilab

Scilab Enterprises
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About

R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be considered as a different implementation of S. There are some important differences, but much code written for S runs unaltered under R. R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, …) and graphical techniques, and is highly extensible. The S language is often the vehicle of choice for research in statistical methodology, and R provides an Open Source route to participation in that activity. One of R’s strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed.

About

Numerical analysis or Scientific computing is the study of approximation techniques for numerically solving mathematical problems. Scilab provides graphics functions to visualize, annotate and export data and offers many ways to create and customize various types of plots and charts. Scilab is a high level programming language for scientific programming. It enables a rapid prototyping of algorithms, without having to deal with the complexity of other more low level programming language such as C and Fortran (memory management, variable definition). This is natively handled by Scilab, which results in a few lines of code for complex mathematical operations, where other languages would require much longer codes. It also comes with advanced data structure such as polynomials, matrices and graphic handles and provides an easily operable development environment.

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

DevOps teams in need of a statistical computing and graphics solution

Audience

Statistical Analysis solution for companies

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

No information available.
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

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Reviews/Ratings

Overall 3.0 / 5
ease 3.0 / 5
features 3.0 / 5
design 3.0 / 5
support 3.0 / 5

Pros & Cons from Real Users

Pros

  • The level of compatibility between Scilab, Matlab and Octave is close to 99% which make transitioning from one to another a very easy task. The portability of your codes between these three packages is straightforward. The learning curve is pretty much flat. Scilab is available on all 3 platforms (Windows, Linux, and Mac OS X)

Cons

  • Overall, Scilab's performance is less consistent than that of Matlab or Octave in most situations. Of course, it depends on what type of problem you're working on, but for my particular needs, I had always better performance (computational time, memory allocation,...) with Octave than with Scilable. Also, one of the limitation is that Scilab, has much less toolboxes and libraries than its two counterparts. If your looking at basic use of Scilab then you will be fine. But if you're an advanced user, you may feel the limitations.

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

The R Foundation
www.r-project.org

Company Information

Scilab Enterprises
www.scilab-enterprises.com

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Alternatives

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ndCurveMaster

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MATLAB

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MatDeck

MatDeck

LabDeck
DataMelt

DataMelt

jWork.ORG
CoPlot

CoPlot

CoHort Software

Categories

Categories

Statistical Analysis Features

Analytics
Association Discovery
Compliance Tracking
File Management
File Storage
Forecasting
Multivariate Analysis
Regression Analysis
Statistical Process Control
Statistical Simulation
Survival Analysis
Time Series
Visualization

Integrations

Akira AI
CIMS Global
Cytel
Decentriq
ERNIE 4.5
GPT-4.5
GPT-4o
GPT-5.3-Codex
Gemini
Gemini 3 Deep Think
Gemini-Exp-1206
Grok 3
Helix Editor
Kimi K2.7 Code
Mistral 7B
Ornith-1.0
Replit Agent
SAS Life Science Analytics Framework
Saagie
Sonatype Nexus Repository

Integrations

Akira AI
CIMS Global
Cytel
Decentriq
ERNIE 4.5
GPT-4.5
GPT-4o
GPT-5.3-Codex
Gemini
Gemini 3 Deep Think
Gemini-Exp-1206
Grok 3
Helix Editor
Kimi K2.7 Code
Mistral 7B
Ornith-1.0
Replit Agent
SAS Life Science Analytics Framework
Saagie
Sonatype Nexus Repository
Claim R and update features and information
Claim R and update features and information
Claim Scilab and update features and information
Claim Scilab and update features and information