Revision 766b6821a98ea206fe461d23237bc4a4589c24af authored by Alireza Mahani on 02 November 2022, 10:02:22 UTC, committed by cran-robot on 02 November 2022, 10:02:22 UTC
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Package: sns
Type: Package
Title: Stochastic Newton Sampler (SNS)
Version: 1.2.2
Date: 2022-11-01
Author: Alireza S. Mahani, Asad Hasan, Marshall Jiang, Mansour T.A. Sharabiani 
Maintainer: Alireza Mahani <>
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 <>.
License: GPL (>= 2)
Imports: mvtnorm, coda, numDeriv
Suggests: RegressionFactory, MfUSampler
NeedsCompilation: no
Repository: CRAN
Packaged: 2022-11-01 19:30:51 UTC; ec2-user
Date/Publication: 2022-11-02 11:02:22 UTC
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