One-Step Estimation
Overview
Provide principally an eponymic function that numerically computes the Le Cam's one-step estimator for an independent and identically distributed sample. One-step estimation is asymptotically efficient (see L. Le Cam (1956) https://projecteuclid.org/euclid.bsmsp/1200501652) and can be computed faster than the maximum likelihood estimator for large observation samples, see e.g. Brouste et al. (2021) doi:10.32614/RJ-2021-044.
- add README
- remove NOTEs
From inst/NEWS.md in the release
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 3includes a package overview page
- Examples that run
- 100%2 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 100%
Downloads
Dependencies
Installing OneStep adds 6 packages (4 with compiled code, 6.2 MB of source tarballs). Heaviest: fitdistrplus 2.4 MB, Rcpp 1.8 MB, RcppArmadillo 1.0 MB.
Code & Tests
People & History
Package metadata
- First published
- 2020-07-13
- Total releases
- 5 / 6 yrs
- License
- GPL (>= 2) OSI
- Download size
- 23 KB
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("OneStep")The package provides a citation file that builds its entry when R runs it. Run citation() to see it.
Cite the R Observatory
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From data release v2026-10-21, which the citation names so these numbers can be found later. More on citing and the projects behind them.