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sns
View on CRAN: Click
here
Download and install sns package within the R console
Install from CRAN:
install.packages("sns")
Install from Github:
library("remotes")
install_github("cran/sns")
Install by package version:
library("remotes")
install_version("sns", "1.2.2")
Attach the package and use:
library("sns")
Maintained by
Alireza Mahani
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2014-08-29
Latest Update: 2022-11-02
Description:
Stochastic Newton Sampler (SNS) is a Metropolis-Hastings-based, Markov Chain Monte Carlo sampler for twice differentiable, log-concave probability density functions (PDFs) where the proposal density function is a multivariate Gaussian resulting from a second-order Taylor-series expansion of log-density around the current point. The mean of the Gaussian proposal is the full Newton-Raphson step from the current point. A Boolean flag allows for switching from SNS to Newton-Raphson optimization (by choosing the mean of proposal function as next point). This can be used during burn-in to get close to the mode of the PDF (which is unique due to concavity). For high-dimensional densities, mixing can be improved via 'state space partitioning' strategy, in which SNS is applied to disjoint subsets of state space, wrapped in a Gibbs cycle. Numerical differentiation is available when analytical expressions for gradient and Hessian are not available. Facilities for validation and numerical differentiation of log-density are provided. Note: Formerly available versions of the MfUSampler can be obtained from the archive <https://cran.r-project.org/src/contrib/Archive/MfUSampler/>.
How to cite:
Alireza Mahani (2014). sns: Stochastic Newton Sampler (SNS). R package version 1.2.2, https://cran.r-project.org/web/packages/sns
Previous versions and publish date:
Other packages that cited sns R package
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Other R packages that sns depends,
imports, suggests or enhances
Functions, R codes and Examples using
the sns R package
Some associated functions: ess . plot.sns . predict.sns . sns.check.logdensity . sns.fghEval.numaug . sns . sns.part . sns.run . summary.sns .
Some associated R codes: ess.R . sns.R . sns.methods.R . zzz.R . Full sns package functions and examples
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