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) .

OneStep: Le Cam's One-Step Estimation

OneStep provides 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)) and can be computed faster than the maximum likelihood estimator for large observation samples

The package

The stable version of OneStep can be installed from CRAN using:

install.packages("OneStep")

Finally load the package in your current R session with the following R command:

library(OneStep)

Documentation

The overall documentation is available at

help(OneStep)