Systems and Means of Informatics
2021, Volume 31, Issue 1, pp 122-132
METHODS FOR COMPARING COMPETING HYPOTHESES IN HYPOTHESIS-ORIENTED SYSTEMS
- E. M. Tirikov
- D. Y. Kovalev
Abstract
With the advent of a new class of virtual experiments management systems, the use of hypotheses and models in an explicit form becomes more and more widespread. Such systems apply both hypotheses generated from the data and theoretical hypotheses. It becomes critically important to compare several competing hypotheses of different origin with each other. The paper considers various approaches to comparing competing hypotheses and computational models implementing them. The considered approaches are implemented as a software component that is a part of a virtual experiment management system. The component is applied for problem solving in neurophysiology.
[+] References (16)
- Kovalev, D., and E. Tarasov. 2019. Virtual experiments in data intensive research. Informatika i ee Primeneniya - Inform. Appl. 13(2): 117-125.
- Kiebel, J., S. Kloppel, N. Weiskopf, andK. J. Friston. 2007. Dynamic causal modeling: A generative model of slice timing in fMRI. Neuroimage 34(4): 1487-1496.
- Kovalev, D., D. Sergeev, E. Tirikov, and N. Ponomareva. 2020. Metody i sredstva analiza signalov golovnogo mozga cheloveka na dannykh funktsional'noy magnitno- rezonansnoy tomografii [Methods and tools for analyzing human brain signals based on functional magnetic resonance imaging data]. Data analytics and management in data intensive domains. Eds. B. K. Thalheim, A. V. Sychev, and S. D. Makhortov. CEUR. 2790:214-229.
- Pham, H. 2006. System software reliability. London: Springer-Verlag. 441 p.
- Pham, H. 2019. A new criterion for model selection. Mathematics 7(12):1215. 12 p.
- Rencher, A. C., and G. B. Schaalje. 2008. Linear models in statistics. New York, NY: John Wiley & Sons. 672 p.
- Mahmoudi, M.R., M. Maleki, and A. Pak. 2018. Testing the equality of two independent regression models. Commun. Stat. A - Theor. 47(12):2919-2926.
- Akaike, H. 1974. A new look at the statistical model identification. IEEE T. Automat. Contr. 19(6):716-723.
- Liddle, A. R. 2007. Information criteria for astrophysical model selection. Mon. Not. R. Astron. Soc. Lett. 377(1):L74-L78.
- Giraud, C. 2014. Introduction to high-dimensional statistics. Boca Raton, FL, USA: CRC Press. 270 p.
- Borges, C.E., C. L. Alonso, and J.L. Montana. 2010. Model selection in genetic programming. 12th Annual Conference on Genetic and Evolutionary Computation Proceedings. New York, NY: ACM. 985-986. doi: 10.1145/1830483.1830662.
- Tarasov, E., and D. Kovalev. 2017. Otsenka kachestva nauchnykh gipotez v virtu- al'nykh eksperimentakh v oblastyakh s intensivnym ispol'zovaniem dannykh [Estima-tion of scientific hypotheses quality in virtual experiments in data intensive domains]. Data analytics and management in data intensive domains. Eds. L. Kalinichenko, Ya. Manolopoulos, N. Skvortsov, and V. Sukhomlin. CEUR. 2022:281-292.
- Wang, Y., C. Squires, A. Belyaeva, and C. Uhler. 2018. Direct estimation of differences in causal graphs. Adv. Neur. Inf. 31:3770-3781.
- Arslan, S., S. I. Ktena, A. Makropoulos, E. C. Robinson, D. Rueckert, and S. Parisot. 2018. Human brain mapping: A systematic comparison of parcellation methods for the human cerebral cortex. Neuroimage 170:5-30.
- Desikan, R.S., F. Segonne, B. Fischl, et al. 2006. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage 31(3):968-980.
- Dixon, W. J., and A. M. Mood. 1946. The statistical sign test. J. Am. Stat. Assoc. 41(236):557-566.
[+] About this article
Title
METHODS FOR COMPARING COMPETING HYPOTHESES IN HYPOTHESIS-ORIENTED SYSTEMS
Journal
Systems and Means of Informatics
Volume 31, Issue 1, pp 122-132
Cover Date
2021-04-20
DOI
10.14357/08696527210110
Print ISSN
0869-6527
Publisher
Institute of Informatics Problems, Russian Academy of Sciences
Additional Links
Key words
virtual experiments management systems; competing hypotheses; comparison of hypotheses
Authors
E. M. Tirikov  and D. Y. Kovalev
Author Affiliations
Institute of Informatics Problems, Federal Research Center "Computer Science
and Control", Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation
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