View source: R/yuima.sampling.R
setSampling | R Documentation |
setSampling
is a constructor for yuima.sampling-class
.
setSampling(Initial = 0, Terminal = 1, n = 100, delta, grid, random = FALSE, sdelta=as.numeric(NULL), sgrid=as.numeric(NULL), interpolation="pt" )
Initial |
Initial time of the grid. |
Terminal |
Terminal time of the grid. |
n |
number of time intervals. |
delta |
mesh size in case of regular time grid. |
grid |
a grid of times for the simulation, possibly empty. |
random |
specify if it is random sampling. See Details. |
sdelta |
mesh size in case of regular space grid. |
sgrid |
a grid in space for the simulation, possibly empty. |
interpolation |
a rule of interpolation in case of subsampling. By default, the previous tick interpolation. See Details. |
The function creates an object of type
yuima.sampling-class
with several slots.
Initial
:initial time of the grid.
Terminal
:terminal time fo the grid.
n
:the number of observations - 1.
delta
:in case of a regular time grid it is the mesh.
grid
:the grid of times.
random
:either FALSE
or the distribution
of the random times.
regular
:indicator of whether the grid is regular or not. For internal use only.
sdelta
:in case of a regular space grid it is the mesh.
sgrid
:the grid in space.
oindex
:in case of interpolation, a vector of indexes corresponding to the original observations used for the approximation.
interpolation
:the name of the interpolation method used.
In case of subsampling, the observations are subsampled on some given
grid
/sgrid
or according to some random
times. When
the original observations do not exist at a give point of the grid they are
obtained by some approximation method. Available methods are "pt"
or
"previous tick"
observation method, "nt"
or "next tick"
observation method, or by l"linear"
interpolation.
In case of interpolation, the slot oindex
contains the vector of indexes
corresponding to the original observations used for the approximation. For the
linear method the index corresponds to the left-most observation.
The slot random
is used as information in case a grid
is
already determined (e.g. n
or delta
, etc. ot the grid
itself are given) or if some subsampling has occurred or if some particular
method which causes a random grid is used in simulation (for example the
space discretized Euler scheme). The slot random
contains a list
of two elements distr
and scale
, where distr
is a
the distribution of independent random times and scale
is either a
scaling constant or a scaling function.
If the grid
of times is deterministic, then random
is FALSE
.
If not specified and random=FALSE
, the slot grid
is filled
automatically by the function. It is eventually modified or created
after the call to the function simulate
.
If delta
is not specified, it is calculated as (Terminal-Initial)/n)
.
If delta
is specified, the Terminal
is adjusted to be equal to
Initial+n*delta
.
The vectors delta
, n
, Initial
and Terminal
may
have different lengths, but then they are extended to the maximal length to
keep consistency. See examples.
If grid
is specified, it takes precedence over all other arguments.
An object of type yuima.sampling-class
.
The YUIMA Project Team
samp <- setSampling(Terminal=1, n=1000) str(samp) samp <- setSampling(Terminal=1, n=1000, delta=0.3) str(samp) samp <- setSampling(Terminal=1, n=1000, delta=c(0.1,0.3)) str(samp) samp <- setSampling(Terminal=1:3, n=1000) str(samp)
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