Entropy based statistical inference for methane emissions released from wetland

Chemometrics and Intelligent Laboratory Systems

Volumn 141, Issue , 2015, Pages 125-133

  Sabolova R ^a,b   Seckarova V ^a,c   Dusek J ^d   Stehlik M ^e,f  

^a CHARLES UNIVERSITY   (Czech Republic)

^b OPEN UNIVERSITY   (United Kingdom)

^c INSTITUTE OF INFORMATION THEORY AND AUTOMATION   (Czech Republic)

^d Global Change Research Centre AS CR vvi   (Czech Republic)

^e JOHANNES KEPLER UNIVERSITY LINZ   (Austria)

^f DEPARTAMENTO DE FÍSICA   (Chile)

Author keywords

Chaos; Entropy; Kullback Leibler (KL) divergence; Pareto distribution; Saddlepoint approximation; Wetland ecosystem

Indexed keywords

METHANE; ORGANIC MATTER;

ARTICLE; CONTROLLED STUDY; CZECH REPUBLIC; ENTROPY; GENETIC VARIABILITY; MAXIMUM LIKELIHOOD METHOD; METHANOGENESIS; METHANOGENIC ARCHAEON; NONPARAMETRIC TEST; STOCHASTIC MODEL; WETLAND;

EID: 84921535474     PISSN: 01697439     EISSN: 18733239     Source Type: Journal    
DOI: 10.1016/j.chemolab.2014.12.008     Document Type: Article

References (34)

1. Jordanova P., Dušek J., Stehlík M. Modeling methane emission by the infinite moving average process. Chemom. Intell. Lab. Syst. 2013, 122:40-49.
2. Schrödinger E. What is Life? 1967, Cambridge University Press, Cambridge.
3. Addiscott T.M. Entropy, non-linearity and hierarchy in ecosystems. Geoderma 2010, 160:57-63.
4. Schlesinger W.H. Biogeochemistry: An Analysis of Global Change 1997, 558. Academic Press, Amsterdam.
5. Le Mer J., Roger P. Production, oxidation, emission and consumption of methane by soils: a review. Eur. J. Soil Biol. 2001, 37(1):25-50.
6. Shukla P.N., Pandey K.D., Mishra V.K. Environmental determinants of soil methane oxidation and methanotrophs. Crit. Rev. Environ. Sci. Technol. 2013, 43:1945-2011.
7. Stehlík M., Střelec L., Thulin M. On robust testing for normality in chemometrics. Chemom. Intell. Lab. Syst. 2003, 130:98-108.
8. Jordanova P., Dušek J., Stehlík M. Microergodicity effects on ebullition of methane modelled by mixed 2 Poisson process with Pareto mixing variable. Chemom. Intell. Lab. Syst. 2013, 128:124-134.
9. Richardson J., Vepraskas M.J. Wetland Soils: Genesis, Hydrology, Landscapes and Classification 2000, Lewis Publishers, USA.
10. Laanbroek H.J. Methane emission from natural wetlands: interplay between emergent macrophytes and soil microbial processes. A mini-review. Ann. Bot. 2010, 105:141-153.
11. Yari G.H., Mohtashami Borzadaran G.R. Entropy for Pareto-types and its order statistics distributions. Commun. Inf. Syst. 2010, 10(3):193-202.
12. Holland M.P., Vitolo R., Rabassa P., Sterk A.E., Broer H. Extreme Value Laws in Dynamical Systems under Physical Observables 1982, (arXiv:1107.5673v1 28 July 2011).
13. Kullback S., Leibler R.A. On information and sufficiency. Ann. Math. Stat. 1951, 22(1):79-86.
14. Kullback S. Information Theory and Statistics 1997, Dover Publications.
15. A. Verster, D.J. De Waal, S. Van Der Merwe, Selecting an optimum threshold with the Kullback-Leibler deviance measure. Available online.
16. Stehlík M. Distributions of exact tests in the exponential family. Metrika 2003, 57:145-164.
17. Stehlík M., Economou P., Kiselak J. Kullback - Leibler life time testing. Appl. Math. Comput. 2014, 240:122-139.
18. Bartlett M.S., Kendall D.G. The statistical analysis of variance-heterogeneity and the logarithmic transformation. Suppl. J. R. Stat. Soc. 1946, 8(1):128-138.
19. Marden J.I. Positions and QQ plots. Stat. Sci. 2004, 19:606-614.
20. Shore J.E., Johnson R.W. Axiomatic derivation of the principle of maximum entropy and the principle of minimum cross-entropy. IEEE Trans. Inf. Theory 1980, 26:26-37.
21. Jaynes T. On the rationale of maximum entropy methods. Proc. IEEE 1982, 70:939-952.
22. Pázman A. Nonlinear Statistical Models 1993, Kluwer Acad. Publ, Dordrecht.
23. Chanton J.P., Whiting G.J. Trace gas exchange in freshwater and coastal marine environments: ebullition and transport by plants. Biogenictrace Gases: Measuring Emissions from Soil and Water 1995, Blackwell, Oxford. P.A. Matson, R.C. Harriss (Eds.).
24. Chen L., Lee C., Mehra R.K. How to tell a bad filter through Monte Carlo simulations. IEEE Trans. Autom. Control 2007, 52:1302-1307.
25. Najm H.N., Debusschere B.J., Marzouk Y.M., Widmer S., Le Maître O.P. Uncertainty quantification in chemical systems. Int. J. Numer. Methods Eng. 2011, 85(5):670.
26. Beckage B., Gross L.J., Kauffman S. The limits to prediction in ecological systems. Ecosphere 2011, 2(art125).
27. May R.M. Simple mathematical models with very complicated dynamics. Nature 1976, 261:459-467.
28. May R.M. Biological populations with nonoverlapping generations: stable points, stable cycles, and chaos. Science 1974, 186:645-647.
29. Hastings A., Hom C., Ellner S., Turchin P., Godfray H. Chaos in ecology - is mother-nature a strange attractor. Annu. Rev. Ecol. Syst. 1993, 24:1-33.
30. Stehlík M. Decompositions of information divergences: recent development, open problems and applications. Am. Inst. Phys. Conf. Proc. 2012, 1493:972-976.
31. Weijs S.V., Van De Giesen N. Accounting for observational uncertainty in forecast verification: an information-theoretical view on forecasts, observations, and truth. Mon. Weather Rev. 2011, 139:2156-2162.
32. Basu A., Mandal A., Martin N., Pardo L. Testing statistical hypotheses based on the density power divergence. Ann. Inst. Stat. Math. 2013, 65:319-348.
33. Bedbur S., Beutner E., Kamps U. Generalized order statistics: an exponential family in model parameters. Stat. J. Theor. Appl. Stat. 2012, 46(2):159-166.
34. Kisslinger A.L., Stummer W. Some Decision Procedures Based on Scaled Bregman Distance Surfaces. GSI 2013, LNCS 8085 2013, 479-486. Springer-Verlag. F. Nielsen, F. Barbaresco (Eds.).