calc_CentralDose

0th

Percentile

Apply the central age model (CAM) after Galbraith et al. (1999) to a given De distribution

This function calculates the central dose and dispersion of the De distribution, their standard errors and the profile log likelihood function for sigma.

Usage
calc_CentralDose(data, sigmab, log = TRUE, plot = TRUE, ...)
Arguments
data

'>RLum.Results or data.frame (required): for data.frame: two columns with De (data[,1]) and De error (data[,2])

sigmab

numeric (with default): additional spread in De values. This value represents the expected overdispersion in the data should the sample be well-bleached (Cunningham & Walling 2012, p. 100). NOTE: For the logged model (log = TRUE) this value must be a fraction, e.g. 0.2 (= 20 %). If the un-logged model is used (log = FALSE), sigmab must be provided in the same absolute units of the De values (seconds or Gray).

log

logical (with default): fit the (un-)logged central age model to De data

plot

logical (with default): plot output

...

further arguments (trace, verbose).

Details

This function uses the equations of Galbraith & Roberts (2012). The parameters delta and sigma are estimated by numerically solving eq. 15 and 16. Their standard errors are approximated using eq. 17. In addition, the profile log-likelihood function for sigma is calculated using eq. 18 and presented as a plot. Numerical values of the maximum likelihood approach are only presented in the plot and not in the console. A detailed explanation on maximum likelihood estimation can be found in the appendix of Galbraith & Laslett (1993, 468-470) and Galbraith & Roberts (2012, 15)

Value

Returns a plot (optional) and terminal output. In addition an '>RLum.Results object is returned containing the following elements:

.$summary

data.frame summary of all relevant model results.

.$data

data.frame original input data

.$args

list used arguments

.$call

call the function call

.$profile

data.frame the log likelihood profile for sigma

The output should be accessed using the function get_RLum

Function version

1.3.2 (2018-01-21 17:22:38)

How to cite

Burow, C. (2018). calc_CentralDose(): Apply the central age model (CAM) after Galbraith et al. (1999) to a given De distribution. Function version 1.3.2. In: Kreutzer, S., Burow, C., Dietze, M., Fuchs, M.C., Schmidt, C., Fischer, M., Friedrich, J. (2018). Luminescence: Comprehensive Luminescence Dating Data Analysis. R package version 0.8.6. https://CRAN.R-project.org/package=Luminescence

References

Galbraith, R.F. & Laslett, G.M., 1993. Statistical models for mixed fission track ages. Nuclear Tracks Radiation Measurements 4, 459-470.

Galbraith, R.F., Roberts, R.G., Laslett, G.M., Yoshida, H. & Olley, J.M., 1999. Optical dating of single grains of quartz from Jinmium rock shelter, northern Australia. Part I: experimental design and statistical models. Archaeometry 41, 339-364.

Galbraith, R.F. & Roberts, R.G., 2012. Statistical aspects of equivalent dose and error calculation and display in OSL dating: An overview and some recommendations. Quaternary Geochronology 11, 1-27.

Further reading

Arnold, L.J. & Roberts, R.G., 2009. Stochastic modelling of multi-grain equivalent dose (De) distributions: Implications for OSL dating of sediment mixtures. Quaternary Geochronology 4, 204-230.

Bailey, R.M. & Arnold, L.J., 2006. Statistical modelling of single grain quartz De distributions and an assessment of procedures for estimating burial dose. Quaternary Science Reviews 25, 2475-2502.

Cunningham, A.C. & Wallinga, J., 2012. Realizing the potential of fluvial archives using robust OSL chronologies. Quaternary Geochronology 12, 98-106.

Rodnight, H., Duller, G.A.T., Wintle, A.G. & Tooth, S., 2006. Assessing the reproducibility and accuracy of optical dating of fluvial deposits. Quaternary Geochronology, 1 109-120.

Rodnight, H., 2008. How many equivalent dose values are needed to obtain a reproducible distribution?. Ancient TL 26, 3-10.

See Also

plot, calc_CommonDose, calc_FiniteMixture, calc_FuchsLang2001, calc_MinDose

Aliases
  • calc_CentralDose
Examples
# NOT RUN {
##load example data
data(ExampleData.DeValues, envir = environment())

##apply the central dose model
calc_CentralDose(ExampleData.DeValues$CA1)

# }
Documentation reproduced from package Luminescence, version 0.8.6, License: GPL-3

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