sns: Stochastic Newton Sampler (SNS)

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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.

Author
Alireza S. Mahani, Asad Hasan, Marshall Jiang, Mansour T.A. Sharabiani
Date of publication
2016-10-25 10:31:12
Maintainer
Alireza Mahani <alireza.s.mahani@gmail.com>
License
GPL (>= 2)
Version
1.1.2

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Man pages

ess
Effective Sample Size Calculator
plot.sns
Plotting "sns" Objects
predict.sns
Sample-based prediction using "sns" Objects
sns
Stochastic Newton Sampler (SNS)
sns.check.logdensity
Utility function for validating log-density
sns.fghEval.numaug
Utility function for augmentation of a log-density function...
sns.part
Utility Functions for Creating and Validating State Space...
sns.run
Drawing multiple samples using Stochastic Newton Sampler
summary.sns
Summarizing "sns" Objects

Files in this package

sns
sns/inst
sns/inst/CITATION
sns/inst/doc
sns/inst/doc/SNS.Rnw
sns/inst/doc/SNS.R
sns/inst/doc/SNS.pdf
sns/NAMESPACE
sns/R
sns/R/sns.R
sns/R/sns.methods.R
sns/R/ess.R
sns/R/zzz.R
sns/vignettes
sns/vignettes/SNS.bib
sns/vignettes/fig_bench_corr_binomial.pdf
sns/vignettes/fig_bench_N_binomial.pdf
sns/vignettes/fig_bench_N_exponential.pdf
sns/vignettes/fig_bench_corr_exponential.pdf
sns/vignettes/SNS.Rnw
sns/vignettes/fig_bench_N_poisson.pdf
sns/vignettes/fig_bench_corr_poisson.pdf
sns/MD5
sns/build
sns/build/vignette.rds
sns/DESCRIPTION
sns/ChangeLog
sns/man
sns/man/plot.sns.Rd
sns/man/sns.fghEval.numaug.Rd
sns/man/summary.sns.Rd
sns/man/predict.sns.Rd
sns/man/sns.part.Rd
sns/man/sns.check.logdensity.Rd
sns/man/sns.run.Rd
sns/man/ess.Rd
sns/man/sns.Rd