Computational statistics
Encyclopedia
Computational statistics, or statistical computing, is the interface between statistics
Statistics
Statistics is the study of the collection, organization, analysis, and interpretation of data. It deals with all aspects of this, including the planning of data collection in terms of the design of surveys and experiments....

 and computer science
Computer science
Computer science or computing science is the study of the theoretical foundations of information and computation and of practical techniques for their implementation and application in computer systems...

. It is the area of computational science
Computational science
Computational science is the field of study concerned with constructing mathematical models and quantitative analysis techniques and using computers to analyze and solve scientific problems...

 (or scientific computing) specific to the mathematical science of statistics
Statistics
Statistics is the study of the collection, organization, analysis, and interpretation of data. It deals with all aspects of this, including the planning of data collection in terms of the design of surveys and experiments....

.

The terms 'computational statistics' and 'statistical computing' are often used interchangeably, although Carlo Lauro (a former president of the International Association for Statistical Computing
International Association for Statistical Computing
The International Association for Statistical Computing was founded during the 41st Session of the International Statistical Institute in 1977, as a Section of the ISI....

) 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
Bootstrapping (statistics)
In statistics, bootstrapping is a computer-based method for assigning measures of accuracy to sample estimates . This technique allows estimation of the sample distribution of almost any statistic using only very simple methods...

, simulation), as well as to cope with analytically intractable problems" [sic
Sic
Sic—generally inside square brackets, [sic], and occasionally parentheses, —when added just after a quote or reprinted text, indicates the passage appears exactly as in the original source...

].

The term 'Computational statistics' may also be used to refer to computationally intensive statistical methods including resampling
Resampling (statistics)
In statistics, resampling is any of a variety of methods for doing one of the following:# Estimating the precision of sample statistics by using subsets of available data or drawing randomly with replacement from a set of data points # Exchanging labels on data points when performing significance...

 methods, Markov chain Monte Carlo
Markov chain Monte Carlo
Markov chain Monte Carlo methods are a class of algorithms for sampling from probability distributions based on constructing a Markov chain that has the desired distribution as its equilibrium distribution. The state of the chain after a large number of steps is then used as a sample of the...

 methods, local regression
Local regression
LOESS, or LOWESS , is one of many "modern" modeling methods that build on "classical" methods, such as linear and nonlinear least squares regression. Modern regression methods are designed to address situations in which the classical procedures do not perform well or cannot be effectively applied...

, kernel density estimation
Kernel density estimation
In statistics, kernel density estimation is a non-parametric way of estimating the probability density function of a random variable. Kernel density estimation is a fundamental data smoothing problem where inferences about the population are made, based on a finite data sample...

, artificial neural networks and generalized additive model
Generalized additive model
In statistics, the generalized additive model is a statistical model developed by Trevor Hastie and Rob Tibshirani for blending properties of generalized linear models with additive models....

s.

Computational statistics journals

  • Communications in Statistics - Simulation and Computation
    Communications in Statistics
    Communications in Statistics is a peer-reviewed scientific journal that publishes papers related to statistics. It is published by Taylor & Francis in two series, Theory and Methods and Simulation and Computation....

  • Computational Statistics
    Computational statistics
    Computational statistics, or statistical computing, is the interface between statistics and computer science. It is the area of computational science specific to the mathematical science of statistics....

  • Computational Statistics & Data Analysis
  • Journal of Computational and Graphical Statistics
    Journal of Computational and Graphical Statistics
    The Journal of Computational and Graphical Statistics is a peer-reviewed scientific journal, published quarterly by the American Statistical Association. Established in 1992, the journal covers the use of computational and graphical methods in statistics and data analysis. The scope includes...

  • Journal of Statistical Computation and Simulation
    Journal of Statistical Computation and Simulation
    Journal of Statistical Computation and Simulation is a peer-reviewed scientific journal that publishes papers related to computational statistics. It is published by Taylor & Francis in English.The journal started publishing in 1972...

  • Journal of Statistical Software
    Journal of Statistical Software
    The Journal of Statistical Software is a peer-reviewed open access scientific journal that publishes papers related to statistical software...

  • Statistics and Computing
  • Wiley Interdisciplinary Reviews Computational Statistics

Associations


Journals

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