Curve Fitting using Unconstrained and Constrained Linear Least Squares Methods
This online calculator build regression model to fit a curve using linear least squares method. If additional constraints on the approximating function are entered, calculator uses Lagrange multipliers to find the solutions.
Artigos que descrevem esta calculadora
Function must pass through particular points
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Digits after the decimal point: 4
Quadratic regression
Correlation coefficient
Coefficient of determination
Average relative error, %
Cubic regression
Correlation coefficient
Coefficient of determination
Average relative error, %
4th order polynomial regression
Correlation coefficient
Coefficient of determination
Average relative error, %
5th order polynomial regression
Correlation coefficient
Coefficient of determination
Average relative error, %
Linear regression
Linear correlation coefficient
Coefficient of determination
Average relative error, %
Logarithmic regression
Correlation coefficient
Coefficient of determination
Average relative error, %
Hyperbolic regression
Correlation coefficient
Coefficient of determination
Average relative error, %
6th order polynomial regression
Correlation coefficient
Coefficient of determination
Average relative error, %
7th order polynomial regression
Correlation coefficient
Coefficient of determination
Average relative error, %
8th order polynomial regression
Correlation coefficient
Coefficient of determination
Average relative error, %
Results
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Calculadoras que utilizam esta calculadora
Calculadora utilizadas por esta calculadora
- Curve Fitting using Unconstrained and Constrained Linear Least Squares Methods
- Random matrix generator
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#polynomial #regression approximation cubic regression curve fit function hyperbolic regression Lagrange linear least squares linear regression logarithmic regression Math polynomial regression quadratic regression regression regression analysis variable
PLANETCALC, Curve Fitting using Unconstrained and Constrained Linear Least Squares Methods
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