Distributed Skew Factor Model Estimation Methods
Overview
Provides a distributed framework for simulating and estimating skew factor models under various skewed and heavy-tailed distributions. The methods support distributed data generation, aggregation of local estimators, and evaluation of estimation performance via mean squared error, relative error, and sparsity measures. The distributed principal component (PC) estimators implemented in the package include 'IPC' (Independent Principal Component),'PPC' (Project Principal Component), 'SPC' (Sparse Principal Component), and other related distributed PC methods. The methodological background follows Guo G. (2023) doi:10.1007/s00180-022-01270-z.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 15
- Examples that run
- 100%13 run in a plain check
- Exported functions with examples
- 82%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 27%
Downloads
Dependencies
Installing DSFM adds 13 packages (5 with compiled code, 5.8 MB of source tarballs). Heaviest: GPArotation 1.6 MB, psych 1.1 MB, quantreg 903 KB.
Code & Tests
Datasets
People & History
- RR 4.6.0 released · 2026-04-24
- 1.0.1Latest2025-12-01 · current release
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2025-12-01
- Total releases
- 1 / 1 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 4.0.0
- Bundled data
- 601 KB / 4 files
- Download size
- 613 KB
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