Example OSL surface exposure dating data
Source:R/Luminescence-package.R
ExampleData.SurfaceExposure.RdA set of synthetic OSL surface exposure dating data to demonstrate the fit_SurfaceExposure functionality. See examples to reproduce the data interactively.
Format
A list with 4 elements:
| Element | Content |
$sample_1 | A data.frame with 3 columns (depth, intensity, error) |
$sample_2 | A data.frame with 3 columns (depth, intensity, error) |
$set_1 | A list of 4 data.frames, each representing a sample with different ages |
$set_2 | A list of 5 data.frames, each representing a sample with different ages |
Details
$sample_1
| mu | sigmaphi | age |
| 0.9 | 5e-10 | 10000 |
$sample_2
| mu | sigmaphi | age | Dose rate | D0 |
| 0.9 | 5e-10 | 10000 | 2.5 | 40 |
$set_1
| mu | sigmaphi | ages |
| 0.9 | 5e-10 | 1e3, 1e4, 1e5, 1e6 |
$set_2
| mu | sigmaphi | ages | Dose rate | D0 |
| 0.9 | 5e-10 | 1e2, 1e3, 1e4, 1e5, 1e6 | 1.0 | 40 |
Examples
## ExampleData.SurfaceExposure$sample_1
sigmaphi <- 5e-10
age <- 10000
mu <- 0.9
x <- seq(0, 10, 0.1)
fun <- exp(-sigmaphi * age * 365.25*24*3600 * exp(-mu * x))
set.seed(666)
synth_1 <- data.frame(depth = x,
intensity = jitter(fun, 1, 0.1),
error = runif(length(x), 0.01, 0.2))
## VALIDATE sample_1
fit_SurfaceExposure(synth_1, mu = mu, sigmaphi = sigmaphi)
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#>
#> [fit_SurfaceExposure()]
#>
#> Estimated paramater(s):
#> -----------------------
#> age (a): 9890 ± 369
#>
#> Fixed parameters(s):
#> --------------------
#> sigmaphi: 5e-10
#> mu: 0.9
#>
#>
#> [RLum.Results-class]
#> originator: fit_SurfaceExposure()
#> data: 5
#> .. $summary : data.frame
#> .. $data : data.frame
#> .. $fit : nls
#> .. $args : list
#> .. $call : call
#> additional info elements: 0
## ExampleData.SurfaceExposure$sample_2
sigmaphi <- 5e-10
age <- 10000
mu <- 0.9
x <- seq(0, 10, 0.1)
Ddot <- 2.5 / 1000 / 365.25 / 24 / 60 / 60 # 2.5 Gy/ka in Seconds
D0 <- 40
fun <- (sigmaphi * exp(-mu * x) *
exp(-(age * 365.25*24*3600) *
(sigmaphi * exp(-mu * x) + Ddot/D0)) + Ddot/D0) /
(sigmaphi * exp(-mu * x) + Ddot/D0)
set.seed(666)
synth_2 <- data.frame(depth = x,
intensity = jitter(fun, 1, 0.1),
error = runif(length(x), 0.01, 0.2))
## VALIDATE sample_2
fit_SurfaceExposure(synth_2, mu = mu, sigmaphi = sigmaphi, Ddot = 2.5, D0 = D0)
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#>
#> [fit_SurfaceExposure()]
#>
#> Estimated paramater(s):
#> -----------------------
#> age (a): 9800 ± 675
#>
#> Fixed parameters(s):
#> --------------------
#> sigmaphi: 5e-10
#> mu: 0.9
#>
#>
#> [RLum.Results-class]
#> originator: fit_SurfaceExposure()
#> data: 5
#> .. $summary : data.frame
#> .. $data : data.frame
#> .. $fit : nls
#> .. $args : list
#> .. $call : call
#> additional info elements: 0
## ExampleData.SurfaceExposure$set_1
sigmaphi <- 5e-10
mu <- 0.9
x <- seq(0, 15, 0.2)
age <- c(1e3, 1e4, 1e5, 1e6)
set.seed(666)
synth_3 <- vector("list", length = length(age))
for (i in 1:length(age)) {
fun <- exp(-sigmaphi * age[i] * 365.25*24*3600 * exp(-mu * x))
synth_3[[i]] <- data.frame(depth = x,
intensity = jitter(fun, 1, 0.05))
}
## VALIDATE set_1
fit_SurfaceExposure(synth_3, age = age, sigmaphi = sigmaphi)
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#>
#> [fit_SurfaceExposure()]
#>
#> Shared estimated paramater(s):
#> -----------------------
#> mu: 0.901 ± 0.00161
#>
#> Fixed parameters(s):
#> --------------------
#> age (a): 1000, 10000, 1e+05, 1e+06
#> sigmaphi: 5e-10
#>
#> To apply the estimated parameters to a sample of unknown age run:
#>
#> fit_SurfaceExposure(data = synth_3, sigmaphi = 5e-10, mu = 0.901)
#>
#>
#> [RLum.Results-class]
#> originator: fit_SurfaceExposure()
#> data: 5
#> .. $summary : data.frame
#> .. $data : data.frame
#> .. $fit : nls
#> .. $args : list
#> .. $call : call
#> additional info elements: 0
## ExampleData.SurfaceExposure$set_2
sigmaphi <- 5e-10
mu <- 0.9
x <- seq(0, 15, 0.2)
age <- c(1e2, 1e3, 1e4, 1e5, 1e6)
Ddot <- 1.0 / 1000 / 365.25 / 24 / 60 / 60 # 2.0 Gy/ka in Seconds
D0 <- 40
set.seed(666)
synth_4 <- vector("list", length = length(age))
for (i in 1:length(age)) {
fun <- (sigmaphi * exp(-mu * x) *
exp(-(age[i] * 365.25*24*3600) *
(sigmaphi * exp(-mu * x) + Ddot/D0)) + Ddot/D0) /
(sigmaphi * exp(-mu * x) + Ddot/D0)
synth_4[[i]] <- data.frame(depth = x,
intensity = jitter(fun, 1, 0.05))
}
## VALIDATE set_2
fit_SurfaceExposure(synth_4, age = age, sigmaphi = sigmaphi, D0 = D0, Ddot = 1.0)
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#>
#> [fit_SurfaceExposure()]
#>
#> Shared estimated paramater(s):
#> -----------------------
#> mu: 0.899 ± 0.00232
#>
#> Fixed parameters(s):
#> --------------------
#> age (a): 100, 1000, 10000, 1e+05, 1e+06
#> sigmaphi: 5e-10
#>
#> To apply the estimated parameters to a sample of unknown age run:
#>
#> fit_SurfaceExposure(data = synth_4, sigmaphi = 5e-10, mu = 0.899)
#>
#>
#> [RLum.Results-class]
#> originator: fit_SurfaceExposure()
#> data: 5
#> .. $summary : data.frame
#> .. $data : data.frame
#> .. $fit : nls
#> .. $args : list
#> .. $call : call
#> additional info elements: 0
if (FALSE) { # \dontrun{
ExampleData.SurfaceExposure <- list(
sample_1 = synth_1,
sample_2 = synth_2,
set_1 = synth_3,
set_2 = synth_4
)
} # }