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OneStep : Le Cam's One-step Estimation Procedure

Author

Listed:
  • Alexandre Brouste

    (LMM - Laboratoire Manceau de Mathématiques - UM - Le Mans Université)

  • Christophe Dutang

    (CEREMADE - CEntre de REcherches en MAthématiques de la DEcision - Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres - CNRS - Centre National de la Recherche Scientifique)

  • Darel Noutsa Mieniedou

    (LMM - Laboratoire Manceau de Mathématiques - UM - Le Mans Université)

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.

Suggested Citation

  • Alexandre Brouste & Christophe Dutang & Darel Noutsa Mieniedou, 2021. "OneStep : Le Cam's One-step Estimation Procedure," Post-Print hal-03452455, HAL.
  • Handle: RePEc:hal:journl:hal-03452455
    DOI: 10.32614/RJ-2021-044
    Note: View the original document on HAL open archive server: https://hal.science/hal-03452455v1
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