calc_TL.MAAD.fit.I: Estimation of the supralinearity value for the MAAD protocol
In dstreble/TLdating: Tools for Thermoluminescence Dating

Description Usage Arguments Details Value Author(s) See Also

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.

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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.