The R Journal: accepted article

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OneStep - Le Cam's one-step estimation procedure PDF download
Alexandre Brouste and Christophe Dutang & Darel Noutsa Mieniedou

Abstract The OneStep package proposes principally an eponymic function that numerically computes Le Cam’s one-step estimator which is asymptotically efficient and can be computed faster than the maximum likelihood estimator for large datasets. Monte-Carlo simulations are carried out for several examples (discrete and continuous probability distributions) in order to exhibit the performance of Le Cam’s one-step estimation procedure in terms of efficiency and computational cost on observation samples of finite size.

Received: 2020-10-27; online 2021-06-08


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@article{RJ-2021-044,
  author = {Alexandre Brouste and Christophe Dutang & Darel Noutsa
          Mieniedou},
  title = {{OneStep - Le Cam's one-step estimation procedure}},
  year = {2021},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2021-044},
  url = {https://journal.r-project.org/archive/2021/RJ-2021-044/index.html}
}