Introduces routines for several linearizable regression models. Introduces several ready-to-be-used linearizable regression models:

• Power model :
• simple linear model :
• simple exponential model :
• multiple linear model :
• Rational function :
• Generalized logistic function :
• Natural logarithm model:

If your data cannot be described with linearizable equation, you should use the TMtxNonLinReg component or NLinRegress routine to retrieve regression coeeficients from fitted equation.

Types

Name	Summary
TRegressionModel	Defines different linear models.

Routines

Name	Summary
ExpDeriv	Derivatives of simple exponential function.
ExpEval	Evaluates exponential function.
ExpFit	Fits simple exponential equation to data.
FracEval	Evaluate rational fraction.
FracFit	Fits rational fraction equation to data.
LineDeriv	Derivatives of linear function.
LineEval	Evaluates linear function.
LineFit	Fits linear equation to data.
LnEval	Evaluate logarithm function.
LnFit	Fits simple logarithm equation to data.
LogisticEval	Evaluate logistic function.
LogisticFit	Fits logistic equation to data.
MulLinEval	Evaluates multiple linear function.
MulLinFit	Fits multiple linear equations to data.
PowerDeriv	Derivatives of power function.
PowerEval	Evaluates power function.
PowerFit	Fits simple exponential equation to data.

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