Computational statistics, or statistical computing, is the interface between statistics, computer science and numerical analysis. It is the area of computational science (or scientific computing) specific to the mathematical science of statistics.

The terms computational statistics and statistical computing are often used interchangeably, although Carlo Lauro (a former president of the International Association for Statistical Computing) proposed making a distinction, defining statistical computing as "the application of computer science to statistics", and computational statistics as "aiming at the design of algorithm for implementing statistical methods on computers, including the ones unthinkable before the computer age (e.g. bootstrap, simulation), as well as to cope with analytically intractable problems" [sic].^[1]

Computational statistics may also be used to refer to computationally-intensive statistical methods including resampling methods, Markov chain Monte Carlo methods, local regression, kernel density estimation and generalized additive models.

Computational statistics journals

• Communications in Statistics - Simulation and Computation
• Computational Statistics
• Computational Statistics & Data Analysis
• Journal of Computational and Graphical Statistics
• Journal of Statistical Computation and Simulation
• Journal of Statistical Software
• Statistics and Computing

References

1. ↑

External links

Associations

• International Association for Statistical Computing
• Statistical Computing section of the American Statistical Association

Journals

• Computational Statistics & Data Analysis
• Journal of Computational & Graphical Statistics
• Statistics and Computing
• Communications in Statistics ? Simulation and Computation
• Journal of Statistical Computation and Simulation

Further reading

Articles

Books

See also

• List of statistical packages