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Description
AMPL stands out as a robust and user-friendly modeling language tailored for the representation and resolution of intricate optimization challenges. It allows users to create mathematical models using a syntax that closely resembles algebraic notation, making it easier to clearly articulate variables, objectives, and constraints in a concise format. This versatile tool accommodates a diverse array of problem types, such as linear programming, nonlinear programming, and mixed-integer programming, among others. A notable advantage of AMPL is its capability to decouple models from their data, which enhances flexibility and scalability when dealing with extensive problems. The platform seamlessly integrates with a variety of solvers, both commercial and open-source, granting users the liberty to select the most suitable solver tailored to their specific requirements. AMPL operates across various operating systems, including Windows, macOS, and Linux, and provides a range of licensing options to accommodate different user preferences. Furthermore, its intuitive design and comprehensive documentation make it accessible even for those who are new to optimization modeling.
Description
NLREG is an advanced statistical analysis tool designed for both linear and nonlinear regression analysis, as well as for fitting curves and surfaces. It identifies the optimal values of parameters for a user-defined equation, ensuring that it best aligns with a given set of data points. Capable of managing various function types, including linear, polynomial, exponential, logistic, periodic, and more general nonlinear forms, NLREG stands out because it can accommodate nearly any algebraically specified function. Unlike many other nonlinear regression tools that are restricted to a limited selection of functions, NLREG offers a comprehensive range of possibilities. The program incorporates a robust programming language with a syntax akin to C, allowing users to define the function to be fitted while enabling the computation of intermediate variables, the use of conditionals, and the implementation of iterative loops. Furthermore, NLREG simplifies the creation of piecewise functions that can adapt their form across different ranges. Additionally, the inclusion of arrays in the NLREG language facilitates the use of tabular lookup methods to designate the function, providing even greater flexibility for users in their analyses. Overall, NLREG is an invaluable asset for statisticians and data analysts seeking to conduct complex fitting tasks.
API Access
Has API
API Access
Has API
Integrations
Artelys Knitro
Python
Pricing Details
$3,000 per year
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
AMPL
Founded
2002
Country
United States
Website
ampl.com/products/ampl/
Vendor Details
Company Name
NLREG
Website
www.nlreg.com
Product Features
Product Features
Statistical Analysis
Analytics
Association Discovery
Compliance Tracking
File Management
File Storage
Forecasting
Multivariate Analysis
Regression Analysis
Statistical Process Control
Statistical Simulation
Survival Analysis
Time Series
Visualization