Package: OneStep 0.9.4

OneStep: One-Step Estimation

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>.

Authors:Alexandre Brouste [aut], Christophe Dutang [aut, cre], Darel Noutsa Mieniedou [ctb]

OneStep_0.9.4.tar.gz
OneStep_0.9.4.zip(r-4.7)OneStep_0.9.4.zip(r-4.6)OneStep_0.9.4.zip(r-4.5)
OneStep_0.9.4.tgz(r-4.6-any)OneStep_0.9.4.tgz(r-4.5-any)
OneStep_0.9.4.tar.gz(r-4.7-any)OneStep_0.9.4.tar.gz(r-4.6-any)
OneStep_0.9.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
OneStep/json (API)
NEWS

# Install 'OneStep' in R:
install.packages('OneStep', repos = c('https://dutangc.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.20 score 2 stars 16 scripts 263 downloads 22 mentions 3 exports 10 dependencies

Last updated from:42fd01175d. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK143
source / vignettesOK156
linux-release-x86_64OK138
macos-release-arm64OK172
macos-oldrel-arm64OK119
windows-develOK107
windows-releaseOK97
windows-oldrelOK94
wasm-releaseOK107

Exports:benchonestepbenchonestep.replicateonestep

Dependencies:extraDistrfitdistrpluslatticeMASSMatrixnumDerivRcppRcppArmadillorlangsurvival