Computational Statistics
Submission Deadline: Dec. 30, 2014
Lead Guest Editor
Rifa El-Khozondar
Department of Physics, Al-Aqsa University, Gaza, Gaza Strip, Palestinian Territories
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Guidelines for Submission
Manuscripts can be submitted until the expiry of the deadline. Submissions must be previously unpublished and may not be under consideration elsewhere.
Papers should be formatted according to the guidelines for authors (see: By submitting your manuscripts to the special issue, you are acknowledging that you accept the rules established for publication of manuscripts, including agreement to pay the Article Processing Charges for the manuscripts. Manuscripts should be submitted electronically through the online manuscript submission system at All papers will be peer-reviewed. Accepted papers will be published continuously in the journal and will be listed together on the special issue website.
Published Papers
Authors: Yibeltal Arega Ashebir, Tewodros Getinet Yirtaw, Anteneh Asmare Godana
Pages: 19-23 Published Online: Mar. 20, 2015
Views 3133 Downloads 204
Authors: Dipo Mahto, Ved Prakash, Krishna Murari Singh, Brajnandan Kumar
Pages: 15-18 Published Online: Feb. 5, 2015
Views 3568 Downloads 179
Authors: Teejan T. El-Khazendar, Rifa J. El-Khozondar
Pages: 9-14 Published Online: Dec. 27, 2014
Views 3574 Downloads 254
Authors: Ebru Demircioğlu, Sevilay Kilmen
Pages: 1-8 Published Online: Aug. 24, 2014
Views 6058 Downloads 255
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 developing rapidly, leading to calls that a broader concept of computing should be taught as part of general statistical education. This journal fosters the publication of applications and methodological research in the field of computational statistics. It provides a forum for computer scientists, mathematicians, and statisticians working in a variety of areas in statistics, including biometrics, econometrics, data analysis, graphics, simulation, algorithms, knowledge-based systems, and Bayesian computing.
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