## Four parameters logistic regression - There and back again

Versión 2.0.0.0 (15.7 KB) por
Fit data points with a four points logistic regression or interpolate data.

2.9K descargas

De GitHub

Four parameters logistic regression.
One big holes into MatLab cftool function is the absence of Logistic Functions. In particular, The Four Parameters Logistic Regression or 4PL nonlinear regression model is commonly used for curve-fitting analysis in bioassays or immunoassays such as ELISA, RIA, IRMA or dose-response curves. It is characterized by it’s classic “S” or sigmoidal shape that fits the bottom and top plateaus of the curve, the EC50, and the slope factor (Hill's slope). This curve is symmetrical around its inflection point. The 4PL equation is:
F(x) = D+(A-D)/(1+(x/C)^B)
where:
A = Minimum asymptote. In a bioassay where you have a standard curve, this can be thought of as the response value at 0 standard concentration.
B = Hill's slope. The Hill's slope refers to the steepness of the curve. It could either be positive or negative.

C = Inflection point. The inflection point is defined as the point on the curve where the curvature changes direction or signs. C is the concentration of analyte where y=(D-A)/2.

D = Maximum asymptote. In an bioassay where you have a standard curve, this can be thought of as the response value for infinite standard concentration.

In this submission there are 2 functions: L4P - to find the 4 parameters and to fit your data (as calibrators...); L4Pinv - to interpolate data of unknown samples onto calibrators curve.

Enjoy!

Created by Giuseppe Cardillo
giuseppe.cardillo-edta@poste.it

To cite this file, this would be an appropriate format: Cardillo G. (2012) Four parameters logistic regression - There and back again https://it.mathworks.com/matlabcentral/fileexchange/38122

### Citar como

Giuseppe Cardillo (2023). Four parameters logistic regression - There and back again (https://github.com/dnafinder/logistic4), GitHub. Recuperado .

##### Compatibilidad con la versión de MATLAB
Se creó con R2014b
Compatible con cualquier versión
Windows macOS Linux

### Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

No se pueden descargar versiones que utilicen la rama predeterminada de GitHub

Versión Publicado Notas de la versión
2.0.0.0