Program type: Shareware
Price $ 49 /
Purchase - Get it Now
File size: 3573 Kb
Install support: Install and Uninstall
OS: Mac OS X
regression or also statistics, stepwise and data or free datafit and cheap heuristic or the curve, good fitting or also curve fitting, curvefitting and nonlinear or free non linear and cheap linear or the correlation, good coefficient or also variables, equation and model or free leastsquares and cheap curve or the model, good auto or also autofit, multivariate
ndCurveMaster for mac OS 1.2.2
[Homepage] - by: TCScienceSof - Download links for ndCurveMaster for mac OS
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ndCurveMaster was designed to find optimum equations to describe empirical data using a regression method.
ndCurveMaster is the first and only program to find the ideal equation to allows the auto fitting of an unlimited number of input variables, for example:
y= a0 + a1*x1^(-11) + a2*x3 + a3*x5^3 + a4*[ln(x8)]^3 + a5*[exp(x1*x4)]^(-2) + a6*x1*x8^2 + a7*ln(x2*x6) + a8*x2*x3*x4.
ndCurveMaster uses heuristic techniques for curve fitting.
The software is designed with the purpose of generating high quality results and output while saving your time in the process.
ndCurveMaster compares very favourably to the competition and does so at a lower price.
- auto fitting of an unlimited number of input variables: x1, x2, x3,..., xn and their combinations: x1*x2, x1*x3, x2*x3,..., xn-1*xn
- heuristic techniques for curve fitting
- user may repeatedly add new equations to any model from ranking list
- user can start stepwise regression procedure with backward elimination the least significant variables of any model from ranking list
- build in set includes 120 array of nonlinear equations
- powerful and easy to use
- unlimited multivariate
- full statistical analysis
- stepwise regression with backward elimination
- history and ranking of results
- copy or save to CSV file options
- any value of significance level alpha,
- video tutorials,
- one licence key valid for Windows and Mac OS systems.
ndCurveMaster uses heuristic techniques for curve fitting and implements scientific algorithms. This improves the discovery of better models. But even when you use the same data set each time:
- the way of finding the best models will be different,
- and the models may be different.
Recent changes in this Minor Update:
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See also in Home and Education: Geometry and Mathematic Analysis