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ndCurveMaster is a Windows application designed to help you discover optimum equations necessary for describing empirical data via the multiple linear regression method.

It can read variables and constants from CSV tables in order to generate the equations and associated graphs.
Find optimum equations to describe empirical data
Following a speedy setup operation that shouldn't give you any trouble, you're welcomed by a simplistic interface where you can get started by opening a CSV file with variables (x, y) and constants. There are two types of CSVs supported: USA/UK format (decimal separator is a full stop, value separator is a comma) and EU format (decimal separator is a comma, value separator is a semicolon).
If the CSV information is correctly identified by the application, then you will be able to select the X variables and Y variable from the list while keeping in mind that ndCurveMaster adds all combinations of the X variables. Plus, you can adjust the significance level (alpha).
Sort equations, save history, and view graphs
The software tool then immediately optimizes the equations, which can be sorted in the main window by ID, r-squared or standard error. It is capable of automatically fitting an unlimited number of input variables and it makes use of heuristics for curve fitting.
There are 120 arrays of non-linear equations built into the program. Graphs can be plotted with the click of a button. Moreover, the output equations can be saved to CSV files for closer inspection and safekeeping.
Failed to read multiple x variables
The application carried out tasks rapidly while remaining light on system resources consumption. However, it failed to read CSV files with more than one x variable in our tests ("Too many variables" error message).
All aspects considered, ndCurveMaster offers a straightforward solution for finding optimum equations to describe empirical data using the multiple linear regression method.
Features :
fully automated process curves to fit your data sets
nonlinear fitting
curve and surface fitting: 2D, 3D, 4D, 5D, 6D, ., n-dimensional fitting
automated discovery of nonlinear equations watch the video
auto data fitting of an unlimited number of fitted variables: ln5(x1), exp(x2)3, x31.35,..., xn and their combinations: x21/2·x40.9, x11.3·x51.4, ln2(x3)·x41.2,...,exp(x6)·x71/3·ln2(xn)
heuristic techniques for data fitting by the use of random iterated or full random search alghorithms
full statistical analysis of every equation
stepwise regression with backward elimination
multicollinearity detection by the use of a Variance inflation factor (VIF)
detect and prevent overfitting
the model with or without an intercept term
user can freely expand or reduce the model
POWERFUL AND EASY TO USE:
import data from CSV, XLSX, XLS, ODS spreadsheets watch the video
history and ranking of results
fast, medium and high detailed search
copy or save to CSV file options
any value of significance level alpha
optimized to deal with large amounts of data
Whats New:
Import data from Excel and OpenOffice spreadsheets

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