Computational statistics

Computational statistics , or statistical computing , is the interface between statistics and computer science . It is the area of computational science (or scientific computing) specific to the mathematical science of statistics . This area is also rapidly expanding to include a broader concept of computing as part of general statistical education . [1]

As in traditional statistics the goal is to transform raw data into knowledge [2] , but the focus lies on the computer intensive statistical methods , such as cases with large sample size and non-homogeneous data sets . [2]

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 statistics “, and ‘computational statistics’ as” unattended before the computer age (eg bootstrap , simulation ), as well as to cope with analytically intractable problems “[ sic ] . [3]

The term ‘Computational statistics’ may be used to également Refer to computationally intensive statistical methods Including resampling methods, Markov Chain Monte Carlo methods, local regression , kernel density estimation , neural networks artificial and additive generalized 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
  • The R Journal
  • Statistics and Computing
  • Wiley Interdisciplinary Reviews Computational Statistics

Associations

  • International Association for Statistical Computing

See also

  • Statistical methods in artificial intelligence
  • Free statistical software
  • List of statistical algorithms
  • List of statistical packages
  • Machine learning

References

  1. Jump up^ Nolan, D.& Lang Temple, D. (2010). “Computing in the Statistics Curricula”, The American Statistician 64(2), pp.97-107.
  2. ^ Jump up to:b Wegman, Edward J. ” Computational Statistics: A New Agenda for Statistical Theory and Practice. ” Journal of the Washington Academy of Sciences , vol. 78, no. 4, 1988, pp. 310-322. JSTOR
  3. Jump up^ Lauro, Carlo (1996), “Computational statistics or statistical computing, is that the question?” , Computational Statistics & Data Analysis , 23 (1): 191-193, doi : 10.1016 / 0167-9473 (96) 88920-1

Further reading

Articles

  • Albert, JH; Gentle, JE (2004), Albert, James H; Gentle, James E, eds., “Special Section: Teaching Computational Statistics,” The American Statistician , 58 : 1-1, doi : 10.1198 / 0003130042872
  • Wilkinson, Leland (2008), “The Future of Statistical Computing (with discussion)”, Technometrics , 50 (4): 418-435, doi : 10.1198 / 004017008000000460

Books

  • Drew, John H .; Evans, Diane L .; Glen, Andrew G .; Lemis, Lawrence M. (2007), Computational Probability: Algorithms and Applications in the Mathematical Sciences , Springer International Series in Operations Research & Management Science, Springer, ISBN  0-387-74675-7
  • Gentle, James E. (2002), Elements of Computational Statistics , Springer, ISBN  0-387-95489-9
  • Gentle, James E .; Härdle, Wolfgang; Mori, Yuichi, eds. (2004), Handbook of Computational Statistics: Concepts and Methods , Springer, ISBN  3-540-40464-3
  • Givens, Geof H .; Hoeting, Jennifer A. (2005), Computational Statistics, Wiley-Interscience, ISBN  978-0-471-46124-1
  • Klemens, Ben (2008) , Princeton University Press, Modeling with Data: Tools and Techniques for Statistical Computing , ISBN  978-0-691-13314-0
  • Monahan, John (2001), Numerical Methods of Statistics , Cambridge University Press, ISBN  978-0-521-79168-7
  • Rose, Colin; Smith, Murray D. (2002), Mathematical Statistics with Mathematics , Springer Texts in Statistics, Springer, ISBN  0-387-95234-9
  • Thisted, Ronald Aaron (1988), Elements of Statistical Computing: Numerical Computation , CRC Press, ISBN  0-412-01371-1
  • Gharieb, Reda. R. (2017), Data Science: Scientific and Statistical Computing , Noor Publishing, ISBN  978-3-330-97256-8