OneStep : Le Cam's One-step Estimation Procedure
Alexandre Brouste, Christophe Dutang and Darel Noutsa Mieniedou
, The R Journal (2021) 13:1, pages 366-377.
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, supplementary material, (5 MiB)@article{RJ-2021-044, author = {Alexandre Brouste and Christophe Dutang and 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://doi.org/10.32614/RJ-2021-044}, pages = {366--377}, volume = {13}, number = {1} }