starting_locs: Random Block Locations

In CovEsts: Nonparametric Estimators for Covariance Functions

Random Block Locations

Description

This function performs random sampling to obtain random starting locations for block bootstrap.

Usage

starting_locs(N, l, k, boot_type = "moving")

Arguments

N	The length of the observation window.
l	The block length considered for bootstrap.
k	The number of blocks considered for bootstrap.
boot_type	What type of block bootstrap should be used, either 'moving' for moving block bootstrap or 'circular' for circular block bootstrap.

Details

This function performs random sampling to obtain random starting locations for block bootstrap. If type = 'moving', the set \{1, \dots, N - \ell + 1\} is randomly sampled, with replacement, k times to obtain random block locations for moving block bootstrap. If type = 'circular', the set \{1, \dots, N\} is randomly sampled, with replacement, k times to obtain random block locations for moving block bootstrap.

Value

A vector of length k whose values are random block locations.

References

Chapters 2.5 and 2.7 in Lahiri, S. N. (2003). Resampling Methods for Dependent Data. Springer. https://doi.org/10.1007/978-1-4757-3803-2

Künsch, H. R. (1989). The Jackknife and the Bootstrap for General Stationary Observations. The Annals of Statistics 17(3), 1217-1241. https://doi.org/10.1214/aos/1176347265

Politis, D. N. & Romano, J. P. (1991). A Circular Block-Resampling Procedure for Stationary Data. In R. LePage & L. Billard, eds, Exploring the Limits of Bootstrap, Wiley, 263-270.

Examples

starting_locs(4, 2, 2)

CovEsts documentation built on Sept. 10, 2025, 10:39 a.m.