calc_CentralDose(data, sigmab, log = TRUE, plot = TRUE, ...)RLum.Results or data.frame
(required): for data.frame: two columns with De
(data[,1]) and De error (data[,2])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).logical (with default): fit the (un-)logged central
age model to De datalogical (with default): plot outputtrace, verbose).RLum.Results object is returned containing the
following element:The output should be accessed using the function
get_RLum
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)
plot, calc_CommonDose,
calc_FiniteMixture, calc_FuchsLang2001,
calc_MinDose
##load example data
data(ExampleData.DeValues, envir = environment())
##apply the central dose model
calc_CentralDose(ExampleData.DeValues$CA1)
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