palm - Fitting Point Process Models via the Palm Likelihood
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.