Entropy based statistical inference for methane emissions released from wetland

Radka Sabolova; Vladimira Seckarova; J. Dusek; Milan Stehlik

doi:10.1016/j.chemolab.2014.12.008

Entropy based statistical inference for methane emissions released from wetland

Radka Sabolova
, Vladimira Seckarova
, J. Dusek
, Milan Stehlik

Department of Data Acquisition and Data Quality

Research output: Contribution to journal › Article › peer-review

Abstract

We concentrate on the paradigm question how much stochasticity and how much chaos are present in the methane emission model. In particular we analyze the residua from the process of methane emissions from wetlands in the sedge-grass marsh, in South Bohemia, Czech Republic. Relation to entropy and a specific version of Kullback–Leibler divergence will be given. A graphical tool to assess the amount of entropy in the system is developed and illustrated on real data from the sedge-grass marsh methane emission.

Original language	English
Pages (from-to)	125-133
Number of pages	9
Journal	Chemometrics and Intelligent Laboratory Systems
Volume	141
DOIs	https://doi.org/10.1016/j.chemolab.2014.12.008
Publication status	Published - 05 Feb 2015

Fields of science

101018 Statistics
101024 Probability theory
101029 Mathematical statistics
509 Other Social Sciences

JKU Focus areas

Computation in Informatics and Mathematics
Engineering and Natural Sciences (in general)

Access to Document

10.1016/j.chemolab.2014.12.008

Cite this

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title = "Entropy based statistical inference for methane emissions released from wetland",

abstract = "We concentrate on the paradigm question how much stochasticity and how much chaos are present in the methane emission model. In particular we analyze the residua from the process of methane emissions from wetlands in the sedge-grass marsh, in South Bohemia, Czech Republic. Relation to entropy and a specific version of Kullback–Leibler divergence will be given. A graphical tool to assess the amount of entropy in the system is developed and illustrated on real data from the sedge-grass marsh methane emission.",

author = "Radka Sabolova and Vladimira Seckarova and J. Dusek and Milan Stehlik",

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T1 - Entropy based statistical inference for methane emissions released from wetland

AU - Sabolova, Radka

AU - Seckarova, Vladimira

AU - Dusek, J.

AU - Stehlik, Milan

PY - 2015/2/5

Y1 - 2015/2/5

N2 - We concentrate on the paradigm question how much stochasticity and how much chaos are present in the methane emission model. In particular we analyze the residua from the process of methane emissions from wetlands in the sedge-grass marsh, in South Bohemia, Czech Republic. Relation to entropy and a specific version of Kullback–Leibler divergence will be given. A graphical tool to assess the amount of entropy in the system is developed and illustrated on real data from the sedge-grass marsh methane emission.

AB - We concentrate on the paradigm question how much stochasticity and how much chaos are present in the methane emission model. In particular we analyze the residua from the process of methane emissions from wetlands in the sedge-grass marsh, in South Bohemia, Czech Republic. Relation to entropy and a specific version of Kullback–Leibler divergence will be given. A graphical tool to assess the amount of entropy in the system is developed and illustrated on real data from the sedge-grass marsh methane emission.

UR - http://www.sciencedirect.com/science/article/pii/S0169743914002615

U2 - 10.1016/j.chemolab.2014.12.008

DO - 10.1016/j.chemolab.2014.12.008

M3 - Article

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JO - Chemometrics and Intelligent Laboratory Systems

JF - Chemometrics and Intelligent Laboratory Systems

ER -

Entropy based statistical inference for methane emissions released from wetland

Abstract

Fields of science

JKU Focus areas

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Applications of Statistical Methods

Cite this

Entropy based statistical inference for methane emissions released from wetland

Abstract

Fields of science

JKU Focus areas

Access to Document

Other files and links

Projects

Applications of Statistical Methods

Cite this