OneStep

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.

Last 30 days

This package has been downloaded 218 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 12 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 3,308 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Jul 21, 2024 with 71 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.