Soft Maximin Estimation for Large Scale Heterogeneous Data
Overview
Efficient procedure for solving the soft maximin problem for large scale heterogeneous data, see Lund, Mogensen and Hansen (2022) doi:10.1111/sjos.12580. Currently Lasso and SCAD penalized estimation is implemented. Note this package subsumes and replaces the SMMA package.
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Documentation
- Help pages
- 6
- Examples that run
- 100%6 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 67%
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Dependencies
Code & Tests
People & History
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- archivedRemoved from CRAN2025-12-25issues were not addressed in time
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- 1.1.12023-01-08 · diff ↗
- 1.1
- RR 4.2.0 released · 2022-04-22
- 1.0.12021-07-22 · diff ↗
- 1.02021-07-19
- RR 4.1.0 released · 2021-05-18
Package metadata
- First published
- 2021-07-19
- Total releases
- 4 / 5 yrs
- License
- MIT + file LICENSE OSI · relicensed from GPL (>= 2) in 1.1
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