Description Usage Arguments Details Value Author(s) See Also
View source: R/calc_TL.MAAD.fit.I.R
Internal function called by analyse_TL.MAAD.
This function estimates the supralinearity correction based on the dose vector and the Lx/Tx vector provided.
See details for more information.
1 2 3 | calc_TL.MAAD.fit.I(LxTx, LxTx.error, doses, slope = NULL,
fitting.parameters = list(fit.method = "LIN", fit.weighted = FALSE,
fit.use.slope = FALSE))
|
LxTx |
numeric (required): Lx/Tx vector |
LxTx.error |
numeric (required): Error for the Lx/Tx vector |
doses |
numeric (required): doses vector |
slope |
list (with default): Property of the additive growth curve. |
fitting.parameters |
list (with default): fitting parameters. See details. |
This function estimates the supralinearity correction based on the doses vector and the Lx/Tx matrix provided.
Different fitting methods are available (LIN
, EXP
, EXP+LIN
or EXP+EXP
).
Morover, the fitting can be weigthed or not.
If the fitting parameter fit.use.slope
is TRUE
, the function will use the data
from slope
to define the fitting curve for the supralinearity correction.
In that case, the supralinearity correction growth curve will be parallel to the additive growth curve.
#' Fitting parameters
The fitting parameters are:
method
character: Fitting method (LIN
, EXP
, EXP+LIN
or EXP+EXP
).
fit.weighted
logical: If the fitting is weighted or not.
fit.use.slope
logical: If the slope of the Q growth curve is reused for the supralinearity correction.
fit.rDoses.min
numeric: lowest regenerative dose used for the fitting.
fit.rDoses.max
numeric: Highest regenerative dose used for the fitting.
Warning: This function is an internal function and should not be used except for development purposes. Internal functions can be heavily modified and even renamed or removed in new version of the package.
The function provides an TLum.Results object containing:
GC
lm: The fitting result.
i
numeric: The supralinearity correction estimation for the given equivalent dose
I.error
numeric: The error for the supralinearity correction estimation
summary
numeric: The parameters of the fitting result.
David Strebler, University of Cologne (Germany).
calc_TL.MAAD.fit.Q, analyse_TL.MAAD.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.