Optimization of parameters of the sigmoid function
Syntax:
[param]=sigm_fit(x,y)
that is the same that
[param]=sigm_fit(x,y,[],[],[]) % no fixed_params, automatic initial_params
[param]=sigm_fit(x,y,fixed_params) % automatic initial_params
[param]=sigm_fit(x,y,[],initial_params) % use it when the estimation is poor
[param]=sigm_fit(x,y,fixed_params,initial_params,plot_flag)
param = [min, max, x50, slope]
if fixed_params=[NaN, NaN , NaN , NaN] % or fixed_params=[]
optimization of "min", "max", "x50" and "slope" (default)
if fixed_params=[0, 1 , NaN , NaN]
optimization of x50 and slope of a sigmoid of ranging from 0 to 1
Additional information in the second output, STAT
[param,stat]=sigm_fit(x,y,fixed_params,initial_params,plot_flag)
Example:
%% generate data vectors (x and y)
fsigm = @(param,xval) param(1)+(param(2)-param(1))./(1+10.^((param(3)-xval)*param(4)))
param=[0 1 5 1]; % "min", "max", "x50", "slope"
x=0:0.1:10;
y=fsigm(param,x) + 0.1*randn(size(x));
%% standard parameter estimation
[estimated_params]=sigm_fit(x,y)
%% parameter estimation with forced 0.5 fixed min
[estimated_params]=sigm_fit(x,y,[0.5 NaN NaN NaN])
%% parameter estimation without plotting
[estimated_params]=sigm_fit(x,y,[],[],0)
Zitieren als
R P (2024). sigm_fit (https://www.mathworks.com/matlabcentral/fileexchange/42641-sigm_fit), MATLAB Central File Exchange. Abgerufen .
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- AI, Data Science, and Statistics > Curve Fitting Toolbox >
- Mathematics and Optimization > Optimization Toolbox >
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Version | Veröffentlicht | Versionshinweise | |
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1.5.0.0 | plot bug fixed
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1.4.0.0 | minmax function used in plotting substituted by min and max functions |
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1.3.0.0 | STAT output variable, with confidence intervals for parameters and distribution |
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1.0.0.0 |