Wiley Interdisciplinary Reviews: Computational Statistics

Cover image for Vol. 6 Issue 2

Edited By: James E. Gentle, James M. Landwehr, and David W. Scott

Online ISSN: 1939-0068

Overview



Aims and Scope


Effective with the 2012 volume, this journal will be published in an online-only format.

WIREs Computational Statistics is a major new scientific publication that supports the information needs of researchers in this field and helps to shape its future development. Its goals are:

- to present the current state of the art of Computational Statistics through an ongoing series of commissioned reviews written by leading researchers

- to capture the crucial interdisciplinary flavor of this field by including articles that address the key topics from the differing perspectives of statistics and computing, and including potential applications areas in technology, biology, physics, geography, and sociology

- to capture the rapid development of Computational Statistics through a systematic program of content updates

- to encourage new participation in this field by presenting its achievements and challenges in an accessible way to a broad audience.

WIREs Computational Statistics will be fully indexed in the major abstracting services, and will be assigned an impact factor in the same way as a journal. WIREs Computational Statistics will offer a comprehensive, coherent, well-structured coverage of the field. It will also be updated in a systematic fashion so that its content remains as current as possible.

WIREs Computational Statistics reviews are structured into different article types:

-Opinions - provide a forum for thought-leaders to offer a more individual perspective

-Overviews - provide a broad and non-technical treatment of important topics suitable for advances students and for researchers without a strong background in the field

-Advanced Reviews - examine key areas of research in a citation-rich format suitable for researchers and advanced students

-Focus Articles - present specific real-world issues, examples and implementations

-Editorial Commentaries - allows WIREs editors to comment on broad research trends in a less formal style

WIREs Computational Statistics has the following top-level category structure:

-Applications of Computational Statistics
-Artificial Intelligence
-Biostatistics and Bioinformatics
-Computational Bayesian Methods
-Computationally Intensive Statistical Methods
-Computer Science Methods
-Data Mining
-Data Structures
-Data Visualization
-Databases
-Machine Learning
-Modeling and Simulation
- Numerical Analysis
-Optimization
-Statistical Methods


Readership


WIREs Computational Statistics is designed in such a way that different subsets of the content will be useful to upper-level undergraduates and postgraduate students, to teaching and research professors in academic programs, to scientists and research managers in industry; moreover, WIREs Computational Statistics will include review and background information useful to scientists entering the field of Computational Statistics.


Keywords


Applications of computational statistics; artificial intelligence; biostatistics and bioinformatics; computational Bayesian methods; computationally intensive statistical methods; computer science methods; data mining; data structures; data visualization; databases; machine learning; modeling and simulation; numerical analysis; optimization; statistical methods.




Abstracting and Indexing Information

  • COMPENDEX (Elsevier)
  • Mathematical Reviews/MathSciNet/Current Mathematical Publications (AMS)
  • SCOPUS (Elsevier)

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