Regression Analysis - CurveFitter 4.5.3
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Regression Analysis - CurveFitter 4.5.3 is a program which has property of performing statistical regression analysis to estimate the values of parameters for linear, multivariate, polynomial, exponential and nonlinear functions. The regression analysis determines the values of the parameters that cause the function to best fit the observed data that you provide. This process is also called curve fitting.
- Any user-defined equations of up to nine parameters and eight variables.
- Linear equations.
- Nonlinear exponential, logarithmic and power equations.
- A 38-digit precision math emulator for properly fitting high order polynomials and rationals.
CurveFitter offers graphically review curve fit results: Once your data have been fit, Curvefitter automatically sorts and plots the fitted equations by the statistical criteria of Standard Error. A residual graph as well as parameter output is generated for the selected fitted equation within the Review Curve Fit window.
Moreover , it is Easy to Use: Curvefitter takes full advantage of the Windows user interface to simplify every aspect of operation -- from data import to output of results. Import data from many popular file formats including Excel, Lotus and ASCII. Once your data are in the editor, create a custom equation set and start the automatic fitting process with a single mouse click. Curvefitter is highly intuitive, easy-to-use and remarkably simple to learn.
- CurveFitter is a powerful statistical analysis program that performs linear and nonlinear regression analysis (i.e. curve fitting). CurveFitter determines the values of parameters for an equation, whose form you specify, that cause the equation to best fit a set of data values.CurveFitter can handle linear, polynomial, exponential, and general nonlinear functions.Unlike many "nonlinear" regression programs that can only handle a limited set of function forms, CurveFitter can handle essentially any function whose form you can specify algebraically.
- CurveFitter performs true nonlinear regression analysis, it does not transform the function into a linear form. As a result, it can handle functions that are impossible to linearize such as: y = (a - c) * exp(-b * x) + c
- Another advantage of handing the function in true nonlinear form is that the minimization of the sum of squared residual values (i.e., "least squares") is based on the true nonlinear value rather than some linearized transformation.
- In addition to computing the optimal values of the parameters to best fit the function to the data, CurveFitter generates plots of the data points and the fitted equation. In addition, it plots the distribution of residual values.
- Pentium Processor.
- Windows 95/98/NT/ME/2000/XP/2003/Vista.
- At least 64 MB of memory.
- 5 MB available disk space.
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