Analysing signal data records extracted from a BIN file.
analyseBINdata(obj_pickBIN, nfchn, nlchn, bg = "late",
me = 2.0, distp = "p", kph = NULL,
kdc = NULL, dcr = NULL, FR.fchn = NULL,
FR.mchn = NULL, FR.lchn = NULL,
signal.type = "LxTx", outfile = NULL)analyseBINdata0(obj_pickBIN, fchn, lchn, bg="late", me=2.0,
distp="p", kph=NULL, kdc=NULL, dcr=NULL,
FR.fchn=NULL, FR.mchn=NULL, FR.lchn=NULL,
signal.type="LxTx", outfile=NULL)
Return an invisible list of S3 class object "analyseBIN" containing the following elements:
a data.frame containing calculated SAR data sets
values used as rejection criteria (0-1 values indicating if Tn is more than 3 sigma above BG or not,
ratio of initial Tn signal to BG and associated standard error, relative standard error of Tn in percent, fast ratio of Tn and associated standard error),
NA is produced if the value can not be calculated. Note that in this function rejection criteria are calculated but not applied
values of Tn and associated standard errors
decay curves for Ln and Tn for different aliquots (grains)
ratios of Tx to Tn for various SAR cycles
aliquot or grain ID (i.e., NO, Position, and Grain)
SARdata is a data.frame containing the following elements if signal.type="LxTx":
| Element | Description | NO |
| aliquot (grain) number | SAR.Cycle | SAR cycle (N, R1, R2, R3, ...) |
Dose | regenerative dose | LxTx |
| sensitivity-corrected regenerative-dose signal | seLxTx | standard error of LxTx |
SARdata contains the following elements if signal.type="Lx":
| Element | Description | NO |
| aliquot (grain) number | SAR.Cycle | SAR cycle (N, R1, R2, R3, ...) |
Dose | regenerative dose | Lx |
| regenerative-dose signal | seLx | standard error of Lx |
SARdata contains the following elements if signal.type="Tx":
| Element | Description | NO |
| aliquot (grain) number | SAR.Cycle | SAR cycle (N, R1, R2, R3, ...) |
Dose | regenerative dose | Tx |
| test-dose signal | seTx | standard error of Tx |
list(required): an object of S3 class "pickBIN" produced by
function pickBINdata
integer(required): number of the first few channels from the initial
part of a decay curve. Number of counts summed over channels
(Delay+1L):(Delay+nfchn) is calculated as the fast-component
plus backgroud signal
integer(required): number of the last few channels from the latter part
of a decay curve. If bg="late", number of counts averaged over channels
(Delay+On-nlchn+1L):(Delay+On) will be calculated as the backgroud
signal, if bg="early", number of counts averaged over channels
(Delay+nfchn+1L):(Delay+nfchn+nlchn) will be calculated as the
backgroud signal. Delay and On are obtained internally from the BIN file.
integer(required): channels used for calculating the fast-component signals
integer(required): channels used for calculating the background counts
character(with default): background subtraction method, i.e.,
bg="early" or bg="late"
numeric(with default): measurement error of Lx (or Tx) in percent
character(with default): distribution of photon counts, distp="p" denotes
Poisson distribution, distp="op" denotes Over Poisson distribution
numeric(optional): correction factor for photon counts
numeric(optional): correction factor for dark counts
numeric(optional): dark count rate
vector(optional): fast-component signal channels, note that those channels are extracted
internally from the "ON" channels,
i.e., FR.fchn=((Delay+1):(Delay+On))[FR.fchn].
Example: FR.fchn=1:5
vector(optional): medium-component signal channels, note that those channels are extracted
internally from the "ON" channels,
i.e., FR.mchn=((Delay+1):(Delay+On))[FR.mchn].
Example: FR.mchn=31:60
vector(optional): background signal channels, note that those channels are extracted
internally from the "ON" channels,
i.e., FR.lchn=((Delay+1):(Delay+On))[FR.lchn].
Example: FR.lchn=201:250
character(with default): type of signal, "LxTx", "Lx", or "Tx"
character(optional): if specified, analysis results (i.e., NO, Position, Grain,
SAR.Cycle, Dose, Init, BG, Lx, seLx, TInit, TBG, Tx, seTx,
LxTx, seLxTx) will be written to a CSV file named "outfile" and saved to the current work directory
Function analyseBINdata is used for signal (i.e., Lx, Tx, and Lx/Tx) calculation.
It provides two protocols for background subtraction (i.e., the early and late background subtraction methods).
Standard error of signals are assessed using two methods: if photon counts are assummed to follow Poisson distributions,
Eqn.(3) of Galbraith (2002) will be applied; if photon counts are over-dispersed, Eqn.(10) of Bluszcz et al. (2015) will be applied.
If arguments FR.fchn, FR.mchn, and FR.lchn are provided, fast ratio will be calculated according to Madsen et al. (2009).
Ballarini M, Wallinga J, Wintle AG, Bos AJJ, 2007. A modified SAR protocol for optical dating of individual grains from young quartz samples. Radiation Measurements, 42(3): 360-369.
Bluszcz A, Adamiec G, Heer AJ, 2015. Estimation of equivalent dose and its uncertainty in the OSL SAR protocol when count numbers do not follow a Poisson distribution. Radiation Measurements, 81: 46-54.
Cunningham AC, Wallinga J, 2010. Selection of integration time intervals for quartz OSL decay curves. Quaternary Geochronology, 5(6): 657-666
Duller GAT, 2016. Analyst (v4.31.9), User Mannual.
Durcan JA, Duller GAT, 2011. The fast ratio: A rapid measure for testing the dominance of the fast component in the initial OSL signal from quartz. Radiation Measurements, 46(10): 1065-1072.
Galbraith R, 2002. A note on the variance of a backround-corrected OSL count. Ancient TL, 20(2): 49-51.
Madsen AT, Duller GAT, Donnelly JP, Roberts HM, Wintle AG, 2009. A chronology of hurricane landfalls at Little Sippewissett Marsh, Massachusetts, USA, using optical dating. Geomorphology, 109(1-2): 36-45.
loadBINdata; pickBINdata; pickSARdata; calED;
calSARED; calSGCED; fitGrowth; lsNORM; BIN
### Example 1 (not run):
# obj_loadBIN <- loadBINdata("foo.bin", view=TRUE)
# obj_pickBIN <- pickBINdata(obj_loadBIN, Position=2, LType="OSL")
# analyseBINdata(obj_pickBIN, nfchn=3, nlchn=20)
### Example 2:
data(BIN)
obj_pickBIN <- pickBINdata(BIN, Position=c(2,4,6,8,10),
LType="OSL", view=FALSE)
obj_analyseBIN <- analyseBINdata(obj_pickBIN, nfchn=4, nlchn=20)
#obj_analyseBIN <- analyseBINdata0(obj_pickBIN, fchn=1:4, nlchn=231:250)
obj_analyseBIN$SARdata
Run the code above in your browser using DataLab