Statistics and Computing
Statistics and Computing is a bi-monthly refereed journal that publishes papers covering the interface between the statistical and computing sciences.
The journal includes techniques for evaluating analytically intractable problems, such as bootstrap resampling, Markov chain Monte Carlo, sequential Monte Carlo, approximate Bayesian computation, search and optimization methods, stochastic simulation and Monte Carlo, graphics, computer environments, statistical approaches to software errors, information retrieval, machine learning, statistics of databases and database technology, huge data sets and big data analytics, computer algebra, graphical models, image processing, tomography, inverse problems and uncertainty quantification.
- 24 Volumes
- 100 Issues
- 1,067 Articles
- 24 Open Access
- 1991 - 2014 Available between
Martyn Plummer (November 2014)
Introduction to “Efficient local updates for undirected graphical models” by F. Stingo, G. Marchetti
Colin Fox (November 2014)
Introduction to “Particle Metropolis-Hastings using gradient and Hessian information” by J. Dahlin, F. Lindsten, T. Schön
Christophe Andrieu (November 2014)
- Journal Title
- Statistics and Computing
- Volume 1 / 1991 - Volume 24 / 2014
- Print ISSN
- Online ISSN
- Springer US
- Additional Links
- Industry Sectors
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