palm

Functions to fit point process models using the Palm likelihood. First proposed by Tanaka, Ogata, and Stoyan (2008) doi:10.1002/bimj.200610339, maximisation of the Palm likelihood can provide computationally efficient parameter estimation for point process models in situations where the full likelihood is intractable. This package is chiefly focused on Neyman-Scott point processes, but can also fit the void processes proposed by Jones-Todd et al. (2019) doi:10.1002/sim.8046. The development of this package was motivated by the analysis of capture-recapture surveys on which individuals cannot be identified—the data from which can conceptually be seen as a clustered point process (Stevenson, Borchers, and Fewster, 2019 doi:10.1111/biom.12983). As such, some of the functions in this package are specifically for the estimation of cetacean density from two-camera aerial surveys.

Last 30 days

This package has been downloaded 175 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 7 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 2,650 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 Sep 11, 2024 with 39 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.