Power Law, Exponential and Logarithmic Fit

versión (20.9 KB) por Jonathan C. Lansey
Finds and plots the linear fit to some data points when plotted on a log scale.

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Actualizada 22 Aug 2014

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logfit(X,Y,graphType), where X is a vector and Y is a vector or a
matrix will plot the data with the axis scaling determined
by graphType as follows: graphType-> xscale, yscale
loglog-> log, log
logx -> log, linear
logy -> linear, log
linear -> linear, linear
A line is then fit to the scaled data in a least squares
See the 'notes' section below for help choosing a method.
logfit(X,Y), will search through all the possible axis scalings and
finish with the one that incurs the least error (with error
measured as least squares on the linear-linear data.)

A power law relationship
[slope, intercept] = logfit(x,y,'loglog');
yApprox = (10^intercept)*x.^(slope);

An exponential relationship
[slope, intercept] = logfit(x,y,'logy');
yApprox = (10^intercept)*(10^slope).^x;

A logarithmic relationship
[slope, intercept] = logfit(x,y,'logx');
yApprox = (intercept)+(slope)*log10(x);

A linear relationship
[slope, intercept] = logfit(x,y,'linear');
yApprox = (intercept)+(slope)*x;

Citar como

Jonathan C. Lansey (2022). Power Law, Exponential and Logarithmic Fit (https://www.mathworks.com/matlabcentral/fileexchange/29545-power-law-exponential-and-logarithmic-fit), MATLAB Central File Exchange. Recuperado .

Compatibilidad con la versión de MATLAB
Se creó con R2010b
Compatible con cualquier versión
Compatibilidad con las plataformas
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