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.

• Addresses the use of statistical concepts in computing science, for example, in machine learning, computer vision and data analytics, as well as the use of computers in data modelling, prediction and analysis
• Publishes original research reports, authoritative review papers, discussion papers, book review and software review sections
• Features special issues dedicated to important and emerging topics or the proceedings of relevant conferences