yuima (version 1.0.81)

subsampling: subsampling

Description

subsampling

Usage

subsampling(x, sampling, ...)

Arguments

x

an yuima-class or yuima.model-class object.

sampling

a yuima.sampling-class object.

...

used to create a sampling structure

Value

• yuima
  a yuima.data-class object.

Details

When subsampling on some grid of times, it may happen that no data is available at the given grid point. In this case it is possible to use several techniques. Different options are avaiable specifying the argument, or the slot, interpolation: [object Object],[object Object],[object Object],[object Object]

Examples

## Set a model
diff.coef.1 <- function(t, x1=0, x2) x2*(1+t)
diff.coef.2 <- function(t, x1, x2=0) x1*sqrt(1+t^2)
cor.rho <- function(t, x1=0, x2=0) sqrt((1+cos(x1*x2))/2)
diff.coef.matrix <- matrix(c("diff.coef.1(t,x1,x2)",
"diff.coef.2(t,x1,x2)*cor.rho(t,x1,x2)", "",
"diff.coef.2(t,x1,x2)*sqrt(1-cor.rho(t,x1,x2)^2)"),2,2)
cor.mod <- setModel(drift=c("",""), diffusion=diff.coef.matrix, 
solve.variable=c("x1", "x2"), xinit=c(3,2))
set.seed(111)

## We first simulate the two dimensional diffusion model
yuima.samp <- setSampling(Terminal=1, n=1200)
yuima <- setYuima(model=cor.mod, sampling=yuima.samp)
yuima.sim <- simulate(yuima)

plot(yuima.sim, plot.type="single")

## random sampling with exponential times
## one random sequence per time series
newsamp <- setSampling(
 random=list(rdist=c( function(x) rexp(x, rate=10), 
  function(x) rexp(x, rate=20))) )
newdata <- subsampling(yuima.sim, sampling=newsamp)
points(get.zoo.data(newdata)[[1]],col="red")
points(get.zoo.data(newdata)[[2]],col="green")


plot(yuima.sim, plot.type="single")

## deterministic subsampling with different
## frequence for each time series
newsamp <- setSampling(delta=c(0.1,0.2))
newdata <- subsampling(yuima.sim, sampling=newsamp)
points(get.zoo.data(newdata)[[1]],col="red")
points(get.zoo.data(newdata)[[2]],col="green")