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Average Ratings 0 Ratings

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ease
features
design
support

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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.

Description

ndCurveMaster, a specialized curve fitting software, is designed to fit curves with multiple variables. It automatically applies nonlinear equations to your datasets. These can be observed or measured values. The software supports curve and surfaces fitting in 2D 3D 4D 5D ..., dimensions. ndCurveMaster is able to handle any data, no matter how complex or how many variables there are. ndCurveMaster, for example, can efficiently derive the optimal equations for a dataset that has six inputs (x1-x6) and a corresponding output Y. For example: Y = a0 - a1 - exp(x1)0.5 + a2 ln(x2)8... + a6 x65.2 to accurately match measured value. ndCurveMaster uses machine learning numerical methods to automatically fit the most suitable nonlinear regression function to your dataset, and discover the relationships between inputs and outputs. This tool supports various curve fitting methods, including linear, polynomial, and nonlinear methods. It also utilizes essential validation and goodness-of-fit tests to ensure accuracy. Additionally, ndCurveMaster provides advanced assessments, such as detecting overfitting and multicollinearity, using tools like the Variance Inflation Factor (VIF) and the Pearson correlation matrix.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Pascal
Python

Integrations

Pascal
Python

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

€289
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

NLREG

Website

www.nlreg.com

Vendor Details

Company Name

SigmaLab Tomas Cepowski

Founded

2017

Country

Poland

Website

www.ndcurvemaster.com

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

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

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