MATHEMATICS FOR APPLICATIONS

	ISSN 1805-3610 (Print) ISSN 1805-3629 (On-line) DOI prefix: 10.13164/ma
Scope Editorial Board Instructions to Authors Indexing Ethics Subscription	Mathematics for applications publishes original papers of a high scientific level in all branches of mathematics with an emphasis on applications of results in mathematics itself and other disciplines. Published by the Institute of Mathematics of Brno University of Technology since 2012, this international journal builds on Publications of Technical and Scientific Papers of the Technical University of Brno (ISBN: 80-214-020-X), a renowned journal published by the University until 1990's. It had provided a platform for the international mathematical community to publish research papers and, after its disappearance, we decided to found a new mathematical journal to continue this service. Issued biannually on an open-access basis, the journal has English as the only language of communication. The manuscripts of papers for publication should by prepared electronically using the journal style – see Instructions for Authors – and sent to ma@fme.vutbr.cz .
Address: Mathematics for Applications Institute of Mathematics Faculty of Mechanical Engineering Brno University of Technology Technická 2896/2 616 69 Brno Czech Republic	Recent Volumes : Vol 8. (2019): No. 1 No. 2 Vol 7. (2018): No. 1 No. 2 Vol 6. (2017): No. 1 No. 2 Vol 5. (2016): No. 1 No. 2 Vol 4. (2015): No. 1 No. 2 Vol 3. (2014): No. 1 No. 2 Vol 2. (2013): No. 1 No. 2 Vol 1. (2012): No. 1 No. 2 Latest Issue Vol. 8. No. 2. (2019) E. Fokoué On the versatility and polyvalence of certain statistical learning machines L. Khinkis On a global measure of nonlinearity and its application in parameter estimation in nonlinear regression DOI: 10.13164/ma.2019.07 S. Raja and E. Fokoué Multi-stage fault warning for large electric grids using anomaly detection and machine learning DOI: 10.13164/ma.2019.08 J. T. Whelan and A. Wodon Prediction and evaluation in College Hockey using the Bradley–Terry–Zermelo model DOI: 10.13164/ma.2019.9 P. Sah and E. Fokoué What do Asian and non-Asian scriptures have in common? An applied statistical machine learning inquiry DOI: 10.13164/ma.2019.10 E. A. Ogundepo and E. Fokoué An empirical demonstration of the no free lunch theorem DOI: 10.13164/ma.2019.11 E. Fokoué On the ubiquity of the Bayesian paradigm in statistical machine learning and data science DOI: 10.13164/ma.2019.12