Abstract
In this article, we discuss an important concept of the generalized Radon–Nikodym derivatives using Choquet integral and its correct treatment. It is consequently used in the definition of generalized \(\phi \)-divergence for fuzzy measures with the emphasis on its proper use. We give several results concerning basic properties of \(\phi \)-divergence. In both concepts, we focus mainly on sufficient conditions for which standard properties copy the additive case. As it is shown, the key role in most of the relevant properties for both derivative as well as divergence is the subadditivity of fuzzy measure.



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Notes
Bernoulli distribution \({\displaystyle \mathrm {Ber}_p(k)=p^{k}(1-p)^{1-k}}.\)
Poisson distribution \(\displaystyle {\mathrm {Poi}_\alpha (k)={\frac{\alpha ^{k}\mathrm {e}^{-\alpha }}{k!}}}\).
Also called 2-alternating, strongly subadditive, concave or strictly subadditive.
Also called 2-monotone, strongly superadditive, convex or strictly superadditive.
Here \(f^+, f^-\) are a positive and negative part of function f given by \(f^+ = \max \{f, 0\}\) and \(f^- = \max \{-f, 0\}=-\min \{f, 0\}\), whereas \(f = f^+ - f^-\) and \(|f|=f^++f^-\).
Supposing \(\mu (\Omega )<\infty \), the dual measure \({\overline{\mu }}\) is defined for all \(A \in {\mathcal {A}}\) as \({\overline{\mu }}(A):=\mu (\Omega )-\mu (\Omega \setminus A).\)
Original Hahn decomposition for a measurable space \((\Omega ,{\mathcal {A}})\) and a signed measure \(\mu \) defined on \({\mathcal {A}}\) states that there exist two measurable sets K and Z such that \(K \cup Z = \Omega \) and \(K \cap Z = \emptyset \) such that for all \(E \in {\mathcal {A}}\) it holds \(\mu (E) \ge 0\) if \(E \subseteq K\) and \(\mu (E) \le 0\) if \(E \subseteq Z\).
In fact, three conditions of dominance can be reduced to two, because \(P \ll \nu \) can be obtained from transitivity.
This assertion holds also for log-convex \(\phi \), i.e. \(\phi \) with property if for all \(x, y \in [a, b]\) and for all \(\lambda \in [0, 1]\) it holds \(\phi (\lambda x + (1 - \lambda ) y) \le \phi (x)^{\lambda } \, \phi (y)^{1 - \lambda }\). It is clear that every log-convex function is convex.
This is clear from the fact that dual measure to subadditive is superadditive and vice versa.
It can be interpreted as a line through 1 while whole \(\phi \) lies above it.
More strict conditions are necessary in this case, so it is not included in the theorem.
Class of divergences that are indexed by convex functions and include both the Euclidean distance and the I-divergence as special cases.
Naming of these two properties is not unified, e.g., in Bogachev (2007) it is called absolute continuity and \((\epsilon , \delta )\)-absolute continuity. In the article, notations \(\ll \) and \(\ll _{\epsilon }\) will be used for better comprehensibility.
measure \(\mu \) is concentrated on A means that \(\mu (A^c) = 0\)
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Acknowledgements
We thank the referees for their valuable comments and suggestions improving previous versions of the paper.
Funding
This work was supported by the Slovak Research and Development Agency under the contract No. APVV-16-0337, Agency of the Ministry of Education, Science, Research and Sports of the Slovak Republic and the Slovak Academy of Sciences under the contract No. VEGA 1/0657/22 and the internal faculty grant No. VVGS-PF-2021-1785.
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Appendix
Appendix
Definition A.1
(Dominance and absolute continuity of measuresFootnote 14)
-
(a)
Measure \(\nu \) is dominated by measure \(\mu \), denoted as \(\nu \ll \mu \), if for every set \(E \in {\mathcal {A}}\)
$$\begin{aligned} \mu (E) = 0 \quad \Rightarrow \quad \nu (E) = 0. \end{aligned}$$(Loosely speaking the \(\mu \)-null sets are also \(\nu \)-null sets.)
-
(b)
Measure \(\nu \) is absolutely continuous with respect to \(\mu \), denoted as \(\nu \ll _{\varepsilon } \mu \), if for every \(E \in {\mathcal {A}}\)
$$\begin{aligned} (\forall \varepsilon> 0) \, (\exists \delta > 0) \,\, \mu (E)< \delta \quad \Rightarrow \quad \nu (E) < \varepsilon . \end{aligned}$$(Loosely speaking the sets of small measure \(\mu \) are also sets of small measure \(\nu \).)
Definition A.2
(Mutual singularity of measures) Two measures \(\mu \) and \(\nu \) are called mutually singular (orthogonal), denoted as \(\mu \perp \nu \), if there exists a set \(A \in {\mathcal {A}}\) such that \(\mu \) is concentratedFootnote 15 on A and \(\nu \) is concentrated on \(A^c.\)
Theorem A.3
(Computation of Choquet integral on half-line (Sugeno 2013)) Let \(\mu \) be a fuzzy measure on \(\Omega \subseteq [0,\infty )\), \(g: {\mathbb {R}}^+ \rightarrow {\mathbb {R}}^+\) be a nonnegative continuous function and \(\mu ([t, \tau ])\) is differentiable function with respect to t. If
-
(I)
g is non-decreasing, the Choquet integral of g with respect to \(\mu \) on \([0, \tau ]\) is represented as
$$\begin{aligned} (C) \int _{[0, \tau ]} g \,{\mathrm {d}}\mu = - \int _{0}^{\tau } \frac{\partial }{\partial t} \mu ([t, \tau ]) g(t) \,{\mathrm {d}}t; \end{aligned}$$ -
(II)
g is non-increasing, the Choquet integral of g with respect to \(\mu \) on \([0, \tau ]\) is represented as
$$\begin{aligned} (C) \int _{[0, \tau ]} g \,{\mathrm {d}}\mu = \int _{0}^{\tau } \frac{\partial }{\partial t} \mu ([0, t)) g(t) \,{\mathrm {d}}t. \end{aligned}$$
Definition A.3
(Weak and strong decomposition property (Graf 1980)) Let \((\Omega , {\mathcal {A}})\) be a measurable space and let \(\mu , \nu : {\mathcal {A}} \rightarrow {\mathbb {R}}^+\) be subadditive fuzzy measures.
-
The pair \((\mu , \nu )\) is said to possess the WDP if for all \(\alpha \in {\mathbb {R}}{^+}\) there exists a set \(E_{\alpha } \in {\mathcal {A}}\) such that
$$\begin{aligned} \alpha \nu _{E_{\alpha }} \le \mu _{E_{\alpha }} \qquad {and} \qquad \alpha \nu _{E_{\alpha }^{C}} \ge \mu _{E_{\alpha }^{C}}. \end{aligned}$$ -
The pair \((\mu , \nu )\) is said to possess the SDP if for all \(\alpha \in {\mathbb {R}}^+\) there exists a set \(E_{\alpha } \in {\mathcal {A}}\) such that the following conditions hold
-
\(\forall E, F \in {\mathcal {A}}: \,\, F \subset E \subset E_{\alpha } \qquad \alpha [\nu (E) - \nu (F)] \le \mu (E) - \mu (F)\)
-
\(\forall E \in {\mathcal {A}} \qquad \alpha [\nu (E) - \nu (E \cap E_{\alpha })] \ge \mu (E) - \mu (E \cap E_{\alpha })\).
Theorem A.4
(Characterization of SDP (Graf 1980)) Let \((\Omega , {\mathcal {A}})\) be a measurable space and let \(\mu , \nu : {\mathcal {A}} \rightarrow {\mathbb {R}}^+\) be subadditive fuzzy measures. Then \((\mu , \nu )\) has the SDP if and only if the following holds
-
(I)
\((\mu , \nu )\) has the WDP.
-
(II)
For every \(\alpha \in {\mathbb {R}}^+\), for every \(E \in {\mathcal {A}}\) with \(\alpha \nu (E) \le \mu (E)\), and for every \(F \in {\mathcal {A}}\) with \(F \subset E\) the inequality
$$\begin{aligned} \alpha \left( \nu (E) - \nu (F) \right) \le \mu (E) - \mu (F) \end{aligned}$$is satisfied.
-
(III)
For every \(\alpha \in {\mathbb {R}}^+\), for every \(E \in {\mathcal {A}}\), and for every \(F \in {\mathcal {A}}\) with \(F \subset E, \, \alpha \nu (F) \le \mu (F)\) and \(\alpha \nu (E/F) \ge \mu (E/F)\) the inequality
$$\begin{aligned} \alpha \left( \nu (E) - \nu (F) \right) \ge \mu (E) - \mu (F) \end{aligned}$$is satisfied.
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Ontkovičová, Z., Kiseľák, J. A way to proper generalization of \(\phi \)-divergence based on Choquet derivatives. Soft Comput 26, 11295–11314 (2022). https://doi.org/10.1007/s00500-022-07381-5
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DOI: https://doi.org/10.1007/s00500-022-07381-5