# sns: Stochastic Newton Sampler (SNS)

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

## 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 |