Xi'an's Og

The latest [June] issue of Statistics & Computing is full of interesting Bayesian and Monte Carlo entries, some of which are even open access!

• Proximal Markov chain Monte Carlo algorithms
  Marcelo Pereyra Pages 745-760

  Download PDF (2992KB) View Article

• A computational procedure for estimation of the mixing time of the random-scan Metropolis algorithm
  David A. Spade Pages 761-781

  Download PDF (969KB) View Article

• Exact estimation of multiple directed acyclic graphs
  Chris J. Oates, Jim Q. Smith, Sach Mukherjee, James Cussens Pages 797-811

  Download PDF (932KB) View Article

• Exact sampling of the unobserved covariates in Bayesian spline models for measurement error problems
  Anindya Bhadra, Raymond J. Carroll Pages 827-840

  Download PDF (2605KB) View Article

• Simultaneous inference in structured additive conditional copula regression models: a unifying Bayesian approach
  Nadja Klein, Thomas Kneib Pages 841-860

  Download PDF (4572KB) View Article

• Computation of Gaussian orthant probabilities in high dimension
  James Ridgway Pages 899-916

  Download PDF (998KB) View Article

This entry was posted on June 29, 2016 at 2:18 pm and is filed under Books, Statistics with tags academic journals, Bayesian computation, Monte Carlo Statistical Methods, Springer-Verlag, Statistics and Computing. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.