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subsampling  

Optimal Subsampling Methods for Statistical Models
View on CRAN: Click here


Download and install subsampling package within the R console
Install from CRAN:
install.packages("subsampling")

Install from Github:
library("remotes")
install_github("cran/subsampling")

Install by package version:
library("remotes")
install_version("subsampling", "0.1.1")



Attach the package and use:
library("subsampling")
Maintained by
Qingkai Dong
[Scholar Profile | Author Map]
First Published: 2024-11-05
Latest Update: 2024-11-05
Description:
Balancing computational and statistical efficiency, subsampling techniques offer a practical solution for handling large-scale data analysis. Subsampling methods enhance statistical modeling for massive datasets by efficiently drawing representative subsamples from full dataset based on tailored sampling probabilities. These probabilities are optimized for specific goals, such as minimizing the variance of coefficient estimates or reducing prediction error.
How to cite:
Qingkai Dong (2024). subsampling: Optimal Subsampling Methods for Statistical Models. R package version 0.1.1, https://cran.r-project.org/web/packages/subsampling. Accessed 17 Feb. 2025.
Previous versions and publish date:
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