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FINAL CALL FOR PAPERS Special Issue on DESIGN OF EXPERIMENTS http://www.cmstatistics.org/CMStatistics2016/docs/Design2015.pdf We are inviting submissions for the special issue of Computational Statistics and Data Analysis that will present new advances in computational methods of designing experiments. Experimental research is essential in many areas of science, e.g. agriculture, biology, chemistry, engineering, medicine and physics. Its efficiency and success depends on the way data are collected and analysed. Statistics plays an important part in such studies. The selection or construction of suitable experimental designs contributes substantially to achieving the necessary validity and accuracy of the experimental results, at a minimum cost. There is therefore increasing interest in computer algorithms finding designs that would be too difficult to construct in an ad hoc fashion. One of the great benefits of many algorithmic methods is that they are very flexible in the design parameters they allow, e.g. mixed numbers of levels, irregularly shaped regions of experimentation or multiple strata. Algorithms may use algebraic ideas or combinatorial construction methods to allow otherwise unfeasible exhaustive searches for the most informative experimental designs. This special issue aims to expand the frontiers of how computational methods can be used to develop useful experimental designs. Key topics are: Adaptive designs Computer experiments Designs for compound optimality criteria Designs for dependent observations Designs for mixed models Experiments with mixtures Multi-tiered experiments Designs for nonlinear models Population designs Response surface methodology Robustness of experimental designs Screening experiments Split-plot and multi-stratum designs Supersaturated designs The papers should have a novel methodological computational statistics or advanced data analytic component in order to be considered for publication. Authors who are uncertain about the suitability of their papers should contact the editors. All submissions must contain original unpublished work not being considered for publication elsewhere. Submissions will be refereed according to standard procedures for Computational Statistics and Data Analysis. Information about the journal can be found at http://www.elsevier.com/locate/csda. The deadline for submissions is 28th February 2016. However, papers can be submitted at any time; and, when they have been received, they will enter the editorial system immediately. Papers for the special issue should be submitted directly to the Elsevier Electronic Submission tool EES: http://ees.elsevier.com/csda In EES please ensure that you select the special issue on Design of Experiments and a Co-Editor responsible for the special issue. For further information please send an email to: [log in to unmask] The special issue editors: Alexander Donev, University of Manchester, UK. E-mail: [log in to unmask] Jesus Lopez-Fidalgo, University of Catilla-La Mancha, Spain. E-mail: [log in to unmask] Douglas Wiens, University of Alberta, Canada. E-mail: [log in to unmask] ________________________________ [http://www.plymouth.ac.uk/images/email_footer.gif]<http://www.plymouth.ac.uk/worldclass> This email and any files with it are confidential and intended solely for the use of the recipient to whom it is addressed. If you are not the intended recipient then copying, distribution or other use of the information contained is strictly prohibited and you should not rely on it. If you have received this email in error please let the sender know immediately and delete it from your system(s). Internet emails are not necessarily secure. While we take every care, Plymouth University accepts no responsibility for viruses and it is your responsibility to scan emails and their attachments. Plymouth University does not accept responsibility for any changes made after it was sent. Nothing in this email or its attachments constitutes an order for goods or services unless accompanied by an official order form. You may leave the list at any time by sending the command SIGNOFF allstat to [log in to unmask], leaving the subject line blank.