modernBoot

CRAN-Published R Package for Modern Resampling Methods

Overview

modernBoot is a CRAN-published R package providing modern, efficient, and computationally fast bootstrap resampling techniques for robust statistical inference.

Key Features

• Efficient computation: Uses vectorized R and optional parallel processing through the future and future.apply packages.
• Multiple CI Methods: Supports percentile, BCa (Bias-Corrected and Accelerated), and bootstrap-t confidence intervals.
• Hypothesis Testing: Includes functions for bootstrap-based hypothesis tests and p-value calculation.
• Advanced Sampling: Implements stratified and block bootstrap for complex data structures.
• Parallel Processing: Built-in support for multi-core processing to speed up computations on large datasets.

Installation

From CRAN

The stable version of modernBoot is available from CRAN:

install.packages("modernBoot")

Development version

The development version can be installed from GitHub:

install.packages("remotes")
# remotes::install_github("ikrakib/modernBoot")
install.packages("modernBoot", repos = c('https://ikrakib.r-universe.dev', 'https://cloud.r-project.org'))

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Quick Example

library(modernBoot)

Generate sample data
set.seed(123)
data <- rnorm(100, mean = 5, sd = 2)

Calculate Bias-Corrected and Accelerated (BCa) bootstrap CI
result_ci <- boot_ci(
              data,
              statistic = mean,
              R = 2000,
              ci = "bca"
             )
             
print(result_ci)

Perform a bootstrap hypothesis test
test_result <- boot_test(data, statistic = mean, null_value = 5.5, R = 2000)
print(test_result)

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Functions by Category

Category 1: Confidence Intervals

• boot_ci(): The primary function for bootstrap confidence intervals (percentile, BCa, bootstrap-t).
• boot_ci_quantile(): Specialized function for quantile-based CIs.

Category 2: Hypothesis Testing

• boot_test(): Performs bootstrap-based hypothesis tests.
• boot_pvalue(): Calculates bootstrap p-values.

Category 3: Advanced Resampling

• bootstrap_sample(): Core function for generating bootstrap samples.
• stratified_boot(): For stratified sampling designs.
• block_boot(): For time-series and clustered data.

Documentation

For detailed examples and function descriptions, see the package manual and vignettes: View the main vignette vignette("modernBoot")

Get help for a specific function ?boot_ci

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Citation

Citation

To cite modernBoot in research, run:

citation("modernBoot")

Current CRAN version: 0.1.1

Package DOI: 10.32614/CRAN.package.modernBoot

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License

MIT License. See the LICENSE file for details.

Author

Ibrahim Kholil Rakib
Email: ikrakib1010@gmail.com
GitHub: @ikrakib
LinkedIn: Ibrahim Kholil Rakib

References

• Efron, B., & Tibshirani, R. J. (1993). An Introduction to the Bootstrap. Chapman and Hall/CRC.
• Davison, A. C., & Hinkley, D. V. (1997). Bootstrap Methods and Their Application. Cambridge University Press.