Results 11 to 20 of about 87 (65)
Robust risk aggregation with neural networks. [PDF]
Abstract We consider settings in which the distribution of a multivariate random variable is partly ambiguous. We assume the ambiguity lies on the level of the dependence structure, and that the marginal distributions are known. Furthermore, a current best guess for the distribution, called reference measure, is available.
Eckstein S, Kupper M, Pohl M.
europepmc +2 more sources
Nearly comonotone approximation [PDF]
This paper obtains estimates on the degree of nearly comonotone approximation which extend and improve the estimate obtained by Newman, Passow, and Raymon. In particular, the restriction that f
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A counterexample in comonotone approximation in $L^p$ space [PDF]
For \(f\in C^k[-1,1]\), \(k\in\mathbb{N}\) fixed, let \(e_n^{(k)} (f)_p\) denote the best approximation to \(f\) in the \(L_p\)-metric by algebraic polynomials \(p_n\) of degree at most \(n\) which are comonotone with \(f\), i.e. by polynomials \(p_n\) with the property \(p_n^{(k)} (x)f^{(k)} (x)\geq 0\) for \(x\in [-1,1]\).
Wu, Xiang, Zhou, Song Ping
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Positive results and counterexamples in comonotone approximation II
Let \(\mathbb{P}_{n}\) be the linear space of polynomials of degree at most \(n-1\). For a continuous function \(f\) in an interval \([a,b]\), the degree of best approximation is denoted by \[ E_{n}(f, [a,b]) = \inf \{ \|f-P_{n}\|_{[a,b]}, P_{n}\in \mathbb{P}_{n}\}. \] For \(s\geq1\), let \(\mathbf{Y}_{s} ([a,b])\) denote the family of all subsets \(Y_{
Dany Leviatan +2 more
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New rational cubic Ball interpolation with one parameter is proposed for shape preserving interpolation such as positivity, monotonicity, and convexity preservations and constrained data lie on the same side of the given straight line. To produce shape preserving interpolant, the data dependent sufficient condition is derived on the parameter.
Samsul Ariffin Abdul Karim +2 more
wiley +1 more source
Sum of Bernoulli Mixtures: Beyond Conditional Independence
We consider the distribution of the sum of Bernoulli mixtures under a general dependence structure. The level of dependence is measured in terms of a limiting conditional correlation between two of the Bernoulli random variables. The conditioning event is that the mixing random variable is larger than a threshold and the limit is with respect to the ...
Taehan Bae +2 more
wiley +1 more source
Comonotonic Approximations for the Sum of Log Unified Skew Normal Random Variables: Application in Finance and Actuarial Science [PDF]
The classical works in finance and insurance for modeling asset returns is the Gaussian model. However, when modeling complex random phenomena, more flexible distributions are needed which are beyond the normal distribution. This is because most of the financial and economic data are skewed and have "fat tails".
Arjun K. Gupta, Mohammad A. Azizb
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Multivariate Fréchet copulas and conditional value‐at‐risk
Based on the method of copulas, we construct a parametric family of multivariate distributions using mixtures of independent conditional distributions. The new family of multivariate copulas is a convex combination of products of independent and comonotone subcopulas.
Werner Hürlimann
wiley +1 more source
Equivalence between various Shape Preserving Approximations of periodic functions
We show that the validity of Jackson-type estimates in comonotone and coconvex approximations of continuous $2\pi$-periodic functions by trigonometric polynomials is equivalent to the validity of the corresponding estimates of approximation by continuous
D. Leviatan, O.V. Motorna, I.O. Shevchuk
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Efficiency in Pure‐Exchange Economies With Risk‐Averse Monetary Utilities
ABSTRACT We study Pareto efficiency in a pure‐exchange economy where agents' preferences are represented by risk‐averse monetary utilities. These coincide with law‐invariant monetary utilities, and they can be shown to correspond to the class of monotone, (quasi‐)concave, Schur concave, and translation‐invariant utility functionals. This covers a large
Mario Ghossoub, Michael B. Zhu
wiley +1 more source

