Package: binspp 0.1.26

Remes Radim

binspp: Bayesian Inference for Neyman-Scott Point Processes

The Bayesian MCMC estimation of parameters for Thomas-type cluster point process with various inhomogeneities. It allows for inhomogeneity in (i) distribution of parent points, (ii) mean number of points in a cluster, (iii) cluster spread. The package also allows for the Bayesian MCMC algorithm for the homogeneous generalized Thomas process. The cluster size is allowed to have a variance that is greater or less than the expected value (cluster sizes are over or under dispersed). Details are described in Dvořák, Remeš, Beránek & Mrkvička (2022) <arxiv:10.48550/arXiv.2205.07946>.

Authors:Mrkvicka Tomas [aut], Dvorak Jiri [aut], Beranek Ladislav [aut], Remes Radim [aut, cre]

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binspp/json (API)

Peer review:

Bug tracker:https://github.com/tomasmrkvicka/binspp/issues

On CRAN:

9 exports 1 stars 0.75 score 26 dependencies 364 downloads

Last updated 2 years agofrom:de6458c050. Checks:OK: 1 NOTE: 8. Indexed: yes.

Exports:estgtpestgtprestintpfirst_stepplot_outputsprint_outputsre_estimatergtprThomasInhom

Dependencies:abindclusterdeldirgoftestlatticeMatrixmgcvmvtnormnlmepolyclipRcppRcppArmadilloRcppEigenrpartspatstatspatstat.dataspatstat.explorespatstat.geomspatstat.linnetspatstat.modelspatstat.randomspatstat.sparsespatstat.univarspatstat.utilstensorVGAM