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*x3*x4 ndCurveMaster software was designed to find optimum equations to describe empirical data using only a multiple linear regression method. ndCurveMaster is the first linear regression program that offers an overfitting detection option. ndCurveMaster uses a test set method to detect and prevent overfitting. ndCurveMaster was tested positive for 500 000 cases and 10 variables. ndCurveMaster compares very favourably to the competition and does so at a lower price. General Features: - 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 - detect and prevent overfitting - optimized to work with large amounts of data - unlimited multivariate - 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 - 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. 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.
|License||Free To Try|
|Installation||Install and Uninstall|
|Keywords||statistics, regression, fit, data, curve, fitting, linear, nonlinear, auto, automated, variable, multi, unlimited, equation, formula, stepwise, backward, heuristic, multiple|
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