field.sub {boodd} | R Documentation |
Subsampling of Random Fields
Description
Performs subsampling of a multidimensional array representing a random field on a lattice. This function applies a specified function to each subsample.
Usage
field.sub(arr, func, length.block, ...)
Arguments
arr |
A multidimensional real-valued array; it represents a random field on a grid of dimension
equals to dimension of the |
func |
A function applied to each subsample. The function should accept the subsample as input and return a vector. |
length.block |
An integer or vector of integers; it specified the block lengths for subsampling. If a scalar is provided, the same block length is used for all dimensions |
... |
An optional additional arguments for the |
Details
The field.sub
function is designed for subsampling a multidimensional array.
The length.block
argument defines the size of each subsample. If length.block
is a scalar,
it applies uniformly across all dimensions of the array. Otherwise, it must
be a vector with a length equal to the number of dimensions in arr
.
The function func
is applied to each subsample,
and the results are returned in a matrix or vector, depending on the output of func
.
Value
Returns a matrix or vector, depending on the output of the func
function. Each row in the matrix
corresponds to the result of applying func
to a subsample.
Since it is not a boodd
object, one cannot apply, for example,
the confint
function to construct a confidence intervals (which depends on the rate of
convergence of the statistic of interest), see example below.
References
Bertail, P. and Dudek, A. (2025). Bootstrap for Dependent Data, with an R package (by Bernard Desgraupes and Karolina Marek) - submitted.
Politis, D.N. Romano, J.P. Wolf, M. (1999). Subsampling, Springer, New York.
See Also
fieldboot
, fieldbootP
, blockboot
, jackVarField
.
Examples
set.seed(1)
# 2-dims array
dlens <- c(100,50)
blens <- c(6,3)
arr <- array(round(rnorm(prod(dlens)),2),dim=dlens)
resu<-field.sub(arr,mean,blens)
hist(resu,nclass=25)
N=length(resu)
lB=length(blens)
conf=mean(arr)-(quantile(resu,c(0.025,0.975))-mean(arr))*sqrt(lB)/sqrt(N)
conf[2:1]