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Power regression

Purpose
Description
Macro Synopsis
Modules
Related Functions
References


Purpose

Power regression.

Description

"Power regression", also known as log-log regression, takes the input signal and fits a function

to it where t is the variable along the x-axis.

The function is based on the function Linear regression, with both axes scaled logarithmically.

Return parameters of Power regression are:


Besides a and b, the corresponding uncertainties sigma a and sigma b and the correlation coefficient r, will appear in the message window. This coefficent is given by

where the overline denotes mean values.

Values of r near 0 indicate poor fitting, whereas good fitting is indicated by values of r near +1 or -1, depending on whether the exponent b of the fitting function is positive or negative.

Warning: Make sure that the input signal does not cross any of the axes x=0 or y=0. Otherwise an error will be produced.


Macro Synopsis

y = PowRegress(x,&a,&b);
signal x,y;
float a,b;


Modules

Statistics

Related Functions

Linear regression, Exponential regression, Multilinear regression, Remove DC, Remove trend, Box-Cox transform, Detrended fluctuation analysis (DFA), Long term correlation analysis (LTCA), Principal component analysis (PCA), R/S statistics.

References

Graybill [12]