View source: R/bremla_prepare.R
bremla_prepare | R Documentation |
Prepares input and formats data for bremla and functions therein.
bremla_prepare(
formula,
data,
nsims = NULL,
reference.label = NULL,
x.label = NULL,
y.label = NULL,
events = NULL,
synchronization = NULL,
control.fit = NULL,
control.sim = NULL,
control.linramp = NULL,
control.transition_dating = NULL,
control.bias = NULL
)
formula |
Formula describing the response and covariates (partial
covariates (phi) can be filled out using |
data |
data.frame including response, all covariates included in
|
nsims |
Number of chronologies to be simulated. |
reference.label |
Character label of reference timescale. Used in |
x.label |
Character label for the x-axis (depth). |
y.label |
Character label for the y-axis (age). |
events |
List object describing the specifics of the climate transitions
used in 'formula'. Must include an item called |
synchronization |
List object describing specifics related to tie-points
and their distribution. If |
control.fit |
List object describing specifics related to the fitting procedure.
See |
control.sim |
List object describing specifics related to simulating chronologies.
See |
control.linramp |
List containing specifications for fitting a linear ramp model to given data.
If used, must include |
control.transition_dating |
List object describing specifics related to
the estimation of a given transition. Must include |
control.bias |
List object describing specifics related to the simulation of
unknown stochastic bias. See |
Returns a list containing data in internal formatting (data
), linear regression formula (ls.formula
), inla formula (formula
), input settings and indices corresponding to climate transitions (.args
) and z_0, y_0 and x_0 (preceeding
)
Eirik Myrvoll-Nilsen, eirikmn91@gmail.com
bremla,bremla_chronology_simulation
require(stats)
set.seed(1)
n <- 1000
phi <- 0.8
sigma <- 1.2
a_lintrend <- 0.3; a_proxy = 0.8
dy_noise <- as.numeric(arima.sim(model=list(ar=c(phi)),n=n,sd=sqrt(1-phi^2)))
lintrend <- seq(from=10,to=15,length.out=n)
proxy <- as.numeric(arima.sim(model=list(ar=c(0.9)),n=n,sd=sqrt(1-0.9^2)))
dy <- a_lintrend*lintrend + a_proxy*proxy + sigma*dy_noise
y0 = 11700;z0=1200
age = y0+cumsum(dy)
depth = 1200 + 1:n*0.05
formula = dy~-1+depth2 + proxy
depth2 = depth^2/depth[1]^2 #normalize for stability
data = data.frame(age=age,dy=dy,proxy=proxy,depth=depth,depth2=depth2)
data = rbind(c(y0,NA,NA,z0,NA),data) #First row is only used to extract y0 and z0.
events=list(locations=c(1210,1220,1240))
control.fit = list(ncores=2,noise="ar1")
synchronization=list(method="gauss")
control.sim=list(synchronized=2,
summary=list(compute=TRUE))
control.bias=NULL
object = bremla_prepare(formula,data,nsims=5000,reference.label="simulated timescale",
events = events,
synchronization=synchronization,
control.fit=control.fit,
control.sim=control.sim,
control.bias=control.bias)
summary(object)
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