calc_MaxDose: Apply the maximum age model to a given De distribution
Description
Function to fit the maximum age model to De data. This is a wrapper function
that calls calc_MinDose() and applies a similiar approach as described
in Olley et al. (2006).Usage
calc_MaxDose(data, sigmab, log = TRUE, par = 3, bootstrap = FALSE,
boundaries, init.values, plot = TRUE, ...)Arguments
data
RLum.Results or data.frame (required):
for data.frame: two columns with De (data[,1]) and
De error (values[,2])sigmab
numeric (required): spread in De values given as a
fraction (e.g. 0.2). This value represents the expected overdispersion in
the data should the sample be well-bleached (Cunningham & Walling 2012log
logical (with default): fit the (un-)logged three parameter
minimum dose model to De datapar
numeric (with default): apply the 3- or 4-parametric minimum age
model (par=3 or par=4).boundaries
list: a named list of boundary values for gamma, sigma and mu
to be used in the optimisation routine
(e.g. list(gamma=c(0.01,100), sigma=c(0.01,5), mu=c(10, 100))). If no values are provided
init.values
numeric (with default): starting values for gamma, sigma, p0 and mu.
Custom values need to be provided in a vector of length three in the form of
c(gamma, sigma, p0).plot
logical (with default): plot output
(TRUE/FALSE)...
further arguments for bootstrapping (bs.M, bs.N, bs.h, sigmab.sd).
See details for their usage.
Function version
0.3 (2014-12-17 12:51:56)Details
Data transformation
To estimate the maximum dose population and its standard error, the three
parameter minimum age model of Galbraith et al. (1999) is adapted. The
measured De values are transformed as follows:
1. convert De values to natural logs
2. multiply the logged data to creat a mirror image of the De distribution
3. shift De values along x-axis by the smallest x-value found to obtain
only positive values
4. combine in quadrature the measurement error associated with each De value
with a relative error specified by sigmab
5. apply the MAM to these data
When all calculations are done the results are then converted
as follows
1. subtract the x-offset
2. multiply the natural logs by -1
3. take the exponent to obtain the maximum dose estimate in Gy
Further documentation
Please see calc_MinDose.References
Arnold, L.J., Roberts, R.G., Galbraith, R.F. & DeLong, S.B., 2009. A revised
burial dose estimation procedure for optical dating of young and modern-age
sediments. Quaternary Geochronology 4, 306-325.
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., 2005. Statistics for Fission Track Analysis, Chapman &
Hall/CRC, Boca Raton.
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.
Olley, J.M., Roberts, R.G., Yoshida, H., Bowler, J.M., 2006. Single-grain
optical dating of grave-infill associated with human burials at Lake Mungo,
Australia. Quaternary Science Reviews 25, 2469-2474.
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.Examples
Run this code## load example data
data(ExampleData.DeValues, envir = environment())
Run the code above in your browser using DataLab