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Rosenbrock
View on CRAN: Click
here
Download and install Rosenbrock package within the R console
Install from CRAN:
install.packages("Rosenbrock")
Install from Github:
library("remotes")
install_github("cran/Rosenbrock") Install by package version:
library("remotes")
install_version("Rosenbrock", "0.1.0") Attach the package and use:
library("Rosenbrock")
Maintained by
Martin Wiegand
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-03-15
Latest Update: 2020-03-15
Description:
New Markov chain Monte Carlo (MCMC) samplers new to be thoroughly tested
and their performance accurately assessed. This requires densities
that offer challenging properties to the novel sampling algorithms.
One such popular problem is the Rosenbrock function. However, while its
shape lends itself well to a benchmark problem, no codified multivariate expansion
of the density exists. We have developed an extension to this class of distributions
and supplied densities and direct sampler functions to assess the performance
of novel MCMC algorithms. The functions are introduced in "An n-dimensional Rosenbrock
Distribution for MCMC Testing" by Pagani, Wiegand and Nadarajah (2019) .
How to cite:
Martin Wiegand (2020). Rosenbrock: Extended Rosenbrock-Type Densities for Markov Chain Monte Carlo (MCMC) Sampler Benchmarking. R package version 0.1.0, https://cran.r-project.org/web/packages/Rosenbrock. Accessed 15 Jul. 2026.
Previous versions and publish date:
(2026-07-09 08:23), 0.1.0 (2020-03-15 11:30)
Other packages that cited Rosenbrock R package
View Rosenbrock citation profile
Other R packages that Rosenbrock depends,
imports, suggests or enhances
Complete documentation for Rosenbrock
Functions, R codes and Examples using
the Rosenbrock R package
Some associated functions: deven . dfull . dhybrid . reven . rhybrid .
Some associated R codes: main.R . Full Rosenbrock package functions and examples
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