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binspp
View on CRAN: Click
here
Download and install binspp package within the R console
Install from CRAN:
install.packages("binspp")
Install from Github:
library("remotes")
install_github("cran/binspp") Install by package version:
library("remotes")
install_version("binspp", "0.2.4") Attach the package and use:
library("binspp")
Maintained by
Remes Radim
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-05-27
Latest Update: 2025-05-05
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
Dvor
How to cite:
Remes Radim (2022). binspp: Bayesian Inference for Neyman-Scott Point Processes. R package version 0.2.4, https://cran.r-project.org/web/packages/binspp. Accessed 10 Oct. 2026.
Previous versions and publish date:
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View binspp citation profile
Other R packages that binspp depends,
imports, suggests or enhances
Complete documentation for binspp
Functions, R codes and Examples using
the binspp R package
Some associated functions: binspp . cov_refor . cov_reserv . cov_slope . cov_tdensity . cov_tmi . estgtp . estgtpr . estintp . first_step . plot_outputs . print_outputs . rThomasInhom . re_estimate . rgtp . trees_N4 . x_left_N4 . x_right_N4 . y_bottom_N4 . y_top_N4 .
Some associated R codes: C_prep.R . C_prep_naive.R . RcppExports.R . binspp-package.R . binspp_auxiliary.R . cov_refor.R . cov_reserv.R . cov_slope.R . cov_tdensity.R . cov_tmi.R . estgtp.R . estgtpr.R . rgenpois.R . rgtp.R . trees_N4.R . x_left_N4.R . x_right_N4.R . y_bottom_N4.R . y_top_N4.R . Full binspp package functions and examples
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