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simdd  

Simulation of Fisher Bingham and Related Directional Distributions
View on CRAN: Click here


Download and install simdd package within the R console
Install from CRAN:
install.packages("simdd")

Install from Github:
library("remotes")
install_github("cran/simdd")

Install by package version:
library("remotes")
install_version("simdd", "1.1-2")



Attach the package and use:
library("simdd")
Maintained by
Kassel Liam Hingee
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-02-22
Latest Update: 2023-10-31
Description:
Simulation methods for the Fisher Bingham distribution on the unit sphere, the matrix Bingham distribution on a Grassmann manifold, the matrix Fisher distribution on SO(3), and the bivariate von Mises sine model on the torus. The methods use an acceptance/rejection simulation algorithm for the Bingham distribution and are described fully by Kent, Ganeiber and Mardia (2018) <doi:10.1080/10618600.2017.1390468>. These methods supersede earlier MCMC simulation methods and are more general than earlier simulation methods. The methods can be slower in specific situations where there are existing non-MCMC simulation methods (see Section 8 of Kent, Ganeiber and Mardia (2018) <doi:10.1080/10618600.2017.1390468> for further details).
How to cite:
Kassel Liam Hingee (2023). simdd: Simulation of Fisher Bingham and Related Directional Distributions. R package version 1.1-2, https://cran.r-project.org/web/packages/simdd. Accessed 21 Nov. 2024.
Previous versions and publish date:
1.1-1 (2023-02-22 16:10)
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Complete documentation for simdd
Functions, R codes and Examples using the simdd R package
Some associated functions: rFisherBingham . simdd-package . 
Some associated R codes: Full simdd package functions and examples
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