inst/app/help/fitting/fitting_options_formula.md
In biodosimetry-uab/biodosetools: An R Shiny Application for Biological Dosimetry
Fitting formula
The objective of curve fitting is to determine those values of the coefficients $C$, $\alpha$ and $\beta$ which best fit the data points.
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For low-LET radiation types there is very strong evidence that the yields of chromosome aberrations or micronuclei ($\lambda$) are related to dose ($D$) by the linear quadratic equation $\lambda = C + \alpha D + \beta D^{2}$.
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For high-LET-radiation, the $\alpha$ term becomes large and eventually the $\beta$ term becomes biologically less relevant and also statistically ‘masked’ and the dose response fits better to a linear equation $\lambda = C + \alpha D$.
The user should check which model fits better with its data. However, because at 0 Gy a certain amount of dicentrics exists (1--2 per thousand cells) it is suggested to fit the data using the intercept value $C$.
biodosimetry-uab/biodosetools documentation built on Jan. 26, 2024, 5:36 p.m.
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Fitting formula
The objective of curve fitting is to determine those values of the coefficients $C$, $\alpha$ and $\beta$ which best fit the data points.
-
For low-LET radiation types there is very strong evidence that the yields of chromosome aberrations or micronuclei ($\lambda$) are related to dose ($D$) by the linear quadratic equation $\lambda = C + \alpha D + \beta D^{2}$.
-
For high-LET-radiation, the $\alpha$ term becomes large and eventually the $\beta$ term becomes biologically less relevant and also statistically ‘masked’ and the dose response fits better to a linear equation $\lambda = C + \alpha D$.
The user should check which model fits better with its data. However, because at 0 Gy a certain amount of dicentrics exists (1--2 per thousand cells) it is suggested to fit the data using the intercept value $C$.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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