Convex-Concave fitting to successively updated data and its application to covid-19 analysis
Author:
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Computational Theory and Mathematics,Control and Optimization,Discrete Mathematics and Combinatorics,Computer Science Applications
Link
https://link.springer.com/content/pdf/10.1007/s10878-022-00867-w.pdf
Reference22 articles.
1. Cullinan MP (2019) Piecewise convex–concave approximation in the mini- max norm. In: Demetriou IC, Pardalos PM (eds) Approximation and Optimization: Algorithms, Complexity and Applications, vol 145. Springer Optimization and Its Applications, New York, pp 83–118 (Springer Nature)
2. Davos DE (2021) Efficient Convex/Concave Data Modelling by FORTRAN software L2CXCV: Analytics, Python Interface Design and Application to pandemic COVID-19 data from November 1st 2020 to February 28th 2021 (Master’s Thesis). Department of Economics, National and Kapodistrian University of Athens. (155 pages)
3. Debecker A, Modis T (2021) Poorly known aspects of attening the curve of covid-19. Technol Forecasting and Social Change, 1–13
4. Demetriou IC (2004) Least squares convex-concave data smoothing. Comput Optim and Appl 29:197–217
5. Demetriou IC (2004) A theorem for piecewise convex-concave data approximation. J of Comput and Applied Mathematics 164–165:245–254
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