growth_model | R Documentation |
The core function of the ShellChron growth model. Uses growth rate and SST (Sea Surface Temperature) sinusoids to model d18O data to be matched with the input. In the ShellChron modeling routine, this function is optimized using the SCEUA algorithm and applied on sliding windows through the dataset to estimate the age of each datapoint
growth_model( pars, T_per = 365, G_per = 365, years = 1, t_int = 1, transfer_function = "KimONeil97", d18Ow = "default", Dsam, Osam, t_maxtemp = 182.5, plot = FALSE, MC = 1000, D_err = NULL, O_err = NULL, return = "SSR" )
pars |
List of parameters for temperature and growth rate sinusoids
|
T_per |
Period of SST sinusoid (in days; default = 365) |
G_per |
Period of growth rate sinusoid (in days; default = 365) |
years |
Number of years to be modeled (default = 1) |
t_int |
Time interval (in days; default = 1) |
transfer_function |
Transfer function used to convert d18Oc to temperature data. |
d18Ow |
Either a single value (constant d18Ow) or a vector of length equal to the period in SST data (365 days by default) containing information about seasonality in d18Ow. Defaults to constant d18Ow of 0 permille VSMOW (the modern mean ocean value) |
Dsam |
Vector of |
Osam |
Vector of |
t_maxtemp |
Timing of the warmest day of the year (in julian day; default = 182.5, or May 26th halfway through the year) |
plot |
Should results of modeling be plotted? |
MC |
Number of Monte Carlo simulations to apply for error propagation Default = 1000 |
D_err |
OPTIONAL: Vector containing errors on |
O_err |
OPTIONAL: Vector containing errors on |
return |
String indicating whether to return just the Sum of Squared Residuals ("SSR") or a matrix containing the results of the model and the propagated uncertainties (if applicable) |
Depending on the value of the "return" parameter either a single value representing the Sum of Squared Residuals ("SSR") as a measure for the closeness of the match between modeled d18O and input values, or a matrix containing the full result of the modeling including propagated uncertainties if applicable.
package dependencies: ggplot2 3.2.1 function dependencies: temperature_curve, d18O_model, growth_rate_curve, mc_err_orth
doi: 10.1016/j.palaeo.2017.09.034
# Set parameters G_amp <- 20 G_per <- 365 G_pha <- 100 G_av <- 15 G_skw <- 70 T_amp <- 20 T_per <- 365 T_pha <- 150 T_av <- 15 pars <- c(T_amp, T_pha, T_av, G_amp, G_pha, G_av, G_skw) d18Ow <- 0 # Create dummy data Dsam <- seq(1, 40, 1) Osam <- sin((2 * pi * (seq(1, 40, 1) - 8 + 30 / 4)) / 30) # Test returning residual sum of squares for optimization SSR <- growth_model(pars, T_per, G_per, Dsam = Dsam, Osam = Osam, return = "SSR") # Test returning full model result resmat <- growth_model(pars, T_per, G_per, Dsam = Dsam, Osam = Osam, return = "result")
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