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binspp (version 0.2.3)

Bayesian Inference for Neyman-Scott Point Processes

Description

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) .

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Install

install.packages('binspp')

Monthly Downloads

236

Version

0.2.3

License

GPL-3

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Repository

https://github.com/tomasmrkvicka/binspp

Maintainer

Remes Radim

Last Published

December 3rd, 2025

Functions in binspp (0.2.3)

Estimate the first-order inhomogeneity

print.output_estinternsp

Text output describing the posterior distributions

Results for Bayesian MCMC estimation of parameters of generalized Thomas process

Estimation of interaction Neyman-Scott point process using auxiliary variable algorithm into Markov chain Monte Carlo.

plot.output_estintp

Graphical output describing the posterior distributions

Estimation of Thomas-type cluster point process with complex inhomogeneities

Simulate a realization of Thomas-type cluster point process with complex inhomogeneities

Simulation of generalized Thomas process

simulate.output_estintp

Simulation from the fitted model

Vertical corners for trees_N4 dataset

Left horizontal corners for trees_N4 dataset

Spanish oak trees

Evaluate unnormalized likelihood for auxiliary variable

Re-estimate the posterior distributions with a different burn-in or a different credibility level.

Obtaining the raw MCMC output

Bottom vertical corners for trees_N4 dataset

Right horizontal corners for trees_N4 dataset

Distance to the reforestration polygon

Calculate parameters for Birth and Death Interaction likelihood functions.

Slope of the area

Distance to the reservoir

Bayesian inference for Neyman-Scott point processes

Auxiliary function which calculates sum values Bayesian MCMC estimation of parameters of generalized Thomas process

Topographic moisture index

Generate auxiliary variable for given proposed parameters.

binspp: Bayesian Inference for Neyman-Scott Point Processes

print.output_estintp

Text output describing the posterior distributions