Computational Statistics

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One of the first uses of computers was the use of statistical algorithms.

Computational Statistics or Statistical Computing describes the interface between statistics and computer science . It is a branch of scientific computing (modern: Scientific Computing ) that relates to statistics, but also includes other areas of applied mathematics.

Content

This area has been developing very rapidly since the general availability of computers. Therefore, in addition to the theoretical-mathematical concepts, relevant content in computer science and applied mathematics should also be part of the statistics training.

The terms Computational Statistics and Statistical Computing are often used synonymously. Carlo Lauro, a past president of the International Association for Statistical Computing , suggested making a distinction between the two terms:

  • Statistical computing is the application of computer science concepts to statistics, e.g. B. in the development of statistical programs or programming languages ​​while
  • Computational Statistics relates more to the design and implementation of statistical algorithms on the computer (e.g. bootstrapping and Monte Carlo simulations ) or the numerical solution of problems that cannot be solved analytically (e.g. optimization problems ).

The term computational statistics also refers to computationally intensive methods of statistics such as B. resampling , Markov chain Monte Carlo method , the non- or semi-parametric regression or density estimation as well as neural networks .

literature

items

  • James H. Albert, James E. Gentle: Special Section: Teaching Computational Statistics . In: The American Statistician . tape 58 , 2004, p. 1-1 , doi : 10.1198 / 0003130042872 .
  • Leland Wilkinson: The Future of Statistical Computing (with discussion) . In: Technometrics . tape 50 , no. 4 , 2008, p. 418-435 , doi : 10.1198 / 004017008000000460 .

Books

  • John H. Drew, Diane L. Evans, Andrew G. Glen, Lawrence M. Lemis: Computational Probability: Algorithms and Applications in the Mathematical Sciences . In: International series in operations research & management science. Springer, New York 2008, ISBN 0-387-74675-7 (English).
  • James E. Gentle: Elements of Computational Statistics . Springer, 2002, ISBN 0-387-95489-9 .
  • James E. Gentle, Wolfgang Härdle , Yuichi Mori: Handbook of Computational Statistics: Concepts and Methods . Springer, 2004, ISBN 3-540-40464-3 .
  • Geof H. Givens, Jennifer A. Hoeting: Computational Statistics . Wiley-Interscience, 2005, ISBN 978-0-471-46124-1 .
  • Ben Klemens: Modeling with Data: Tools and Techniques for Statistical Computing . Princeton University Press, 2008, ISBN 978-0-691-13314-0 .
  • John Monahan: Numerical Methods of Statistics . Cambridge University Press, 2001, ISBN 978-0-521-79168-7 .
  • Colin Rose, Murray D. Smith: Mathematical Statistics with Mathematica . Springer, 2002, ISBN 0-387-95234-9 .
  • Ronald Aaron Thisted: Elements of Statistical Computing: Numerical Computation . CRC Press, 1988, ISBN 0-412-01371-1 .

Web links

Societies

Magazines

Individual evidence

  1. ↑ Deborah Nolan, Duncan Temple Lang: Computing in the Statistics Curricula . In: The American Statistician . tape 64 , no. 2 , 2010, p. 97-107 ( berkeley.edu [PDF; accessed April 13, 2013]).
  2. ^ Carlo Lauro: Computational statistics or statistical computing, is that the question? In: Computational Statistics & Data Analysis . tape 23 , 1996, pp. 191-193 , doi : 10.1016 / 0167-9473 (96) 88920-1 .