doserate {gamma}

Dose Rate Estimation

Description

dose_fit builds a calibration curve for gamma dose rate estimation.

Usage

dose_fit(object, background, doses, ...)

dose_predict(object, spectrum, ...)

## S4 method for signature 'GammaSpectra,GammaSpectrum,matrix'
dose_fit(
  object,
  background,
  doses,
  range_Ni,
  range_NiEi,
  details = list(authors = "", date = Sys.time())
)

## S4 method for signature 'GammaSpectra,GammaSpectrum,data.frame'
dose_fit(
  object,
  background,
  doses,
  range_Ni,
  range_NiEi,
  details = list(authors = "", date = Sys.time())
)

## S4 method for signature 'CalibrationCurve,missing'
dose_predict(object, sigma = 1, epsilon = 1.5)

## S4 method for signature 'CalibrationCurve,GammaSpectrum'
dose_predict(object, spectrum, sigma = 1, epsilon = 1.5)

## S4 method for signature 'CalibrationCurve,GammaSpectra'
dose_predict(object, spectrum, sigma = 1, epsilon = 1.5)

Arguments

object

A GammaSpectra or CalibrationCurve object.

background

A GammaSpectrum object of a length-two numeric vector giving the background noise integration value and error, respectively.

doses

A matrix or data.frame TODO.

...

Currently not used.

spectrum

An optional GammaSpectrum or GammaSpectra object in which to look for variables with which to predict. If omitted, the fitted values are used.

range_Ni, range_NiEi

A length-two numeric vector giving the energy range to integrate within (in keV).

details

A list of length-one vector specifying additional informations about the instrument for which the curve is built.

sigma

A numeric value giving TODO.

epsilon

A numeric value giving an extra error term introduced by the calibration of the energy scale of the spectrum.

Details

dose_predict predicts in situ gamma dose rate.

To estimate the gamma dose rate, one of the calibration curves distributed with this package can be used. These built-in curves are in use in several luminescence dating laboratories and can be used to replicate published results. As these curves are instrument specific, the user may have to build its own curve.

The construction of a calibration curve requires a set of reference spectra for which the gamma dose rate is known and a background noise measurement. First, each reference spectrum is integrated over a given interval, then normalized to active time and corrected for background noise. The dose rate is finally modelled by the integrated signal value used as a linear predictor (York et al., 2004).

See vignette(doserate) for a reproducible example.

Value

• dose_fit() returns a CalibrationCurve object.

• dose_predict() returns a data.frame with the following columns:

  name

  (character) the name of the spectra.

  ⁠*_signal⁠

  (numeric) the integrated signal value (according to the value of threshold; see signal_integrate()).

  ⁠*_error⁠

  (numeric) the integrated signal error value (according to the value of threshold; see signal_integrate()).

  gamma_signal

  (numeric) the predicted gamma dose rate.

  gamma_error

  (numeric) the predicted gamma dose rate error.

Author(s)

N. Frerebeau

References

Mercier, N. & Falguères, C. (2007). Field Gamma Dose-Rate Measurement with a NaI(Tl) Detector: Re-Evaluation of the "Threshold" Technique. Ancient TL, 25(1), p. 1-4.

York, D., Evensen, N. M., Martínez, M. L. & De Basabe Delgado, J. (2004). Unified Equations for the Slope, Intercept, and Standard Errors of the Best Straight Line. American Journal of Physics, 72(3), p. 367-75. doi:10.1119/1.1632486.

See Also

signal_integrate()

Examples

## Import CNF files
## Spectra
spc_dir <- system.file("extdata/BDX_LaBr_1/calibration", package = "gamma")
spc <- read(spc_dir)

## Background
bkg_dir <- system.file("extdata/BDX_LaBr_1/background", package = "gamma")
bkg <- read(bkg_dir)

## Get dose rate values
data("clermont")
(doses <- clermont[, c("gamma_dose", "gamma_error")])

## Build the calibration curve
calib_curve <- dose_fit(spc, bkg, doses,
                        range_Ni = c(300, 2800),
                        range_NiEi = c(165, 2800))

## Plot the curve
plot(calib_curve, threshold = "Ni")

## Estimate gamma dose rates
dose_predict(calib_curve, spc)