An Optimal Subset Selection for Distributed Hypothesis Testing
Overview
In the era of big data, data redundancy and distributed characteristics present novel challenges to data analysis. This package introduces a method for estimating optimal subsets of redundant distributed data, based on PPCDT (Conjunction of Power and P-value in Distributed Settings). Leveraging PPC technology, this approach can efficiently extract valuable information from redundant distributed data and determine the optimal subset. Experimental results demonstrate that this method not only enhances data quality and utilization efficiency but also assesses its performance effectively. The philosophy of the package is described in Guo G. (2020) doi:10.1007/s00180-020-00974-4.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 1
- Examples that run
- 100%1 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 0%
Downloads
Dependencies
Installing PPCDT adds no packages beyond those that come with R.
Code & Tests
People & History
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- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- 0.2.0Latest
- 0.1.02024-05-25
- RR 4.4.0 released · 2024-04-24
Package metadata
- First published
- 2024-05-25
- Total releases
- 2 / 2 yrs
- License
- Apache License (== 2.0) · relicensed from MIT + file LICENSE in 0.2.0
- Minimum R
- ≥ 3.5.0
- Download size
- 2.4 KB
Cite
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