Results 51 to 60 of about 18,205 (197)
Sequential Outlier Detection in Nonstationary Time Series
ABSTRACT A novel method for sequential outlier detection in nonstationary time series is proposed. The method tests the null hypothesis of “no outlier” at each time point, addressing the multiple testing problem by bounding the error probability of successive tests, using extreme‐value theory. The asymptotic properties of the test statistic are studied
Florian Heinrichs +2 more
wiley +1 more source
We consider a decision-making problem to evaluate absolute ratings of alternatives from the results of their pairwise comparisons according to two criteria, subject to constraints on the ratings.
Nikolai Krivulin
doaj +1 more source
Confidence Intervals for Price Discovery
ABSTRACT This paper discusses asymptotic and bootstrap confidence intervals for multivariate permanent‐transitory decompositions of cointegrated vector autoregressive I(1) systems, with a focus on price discovery. Alternative estimators of the permanent components are compared in terms of efficiency also under separable linear restrictions on the ...
Heino Bohn Nielsen +2 more
wiley +1 more source
Abstract This paper presents a two‐stage model for planning a renewable energy portfolio by balancing economic, social and environmental sustainability goals. The first stage addresses a multi‐objective problem where conflictive impacts generated by the energy portfolios should be optimised according to the corresponding economic, social or ...
Amelia Bilbao‐Terol +2 more
wiley +1 more source
Fourier Mass Lower Bounds for Batchelor‐Regime Passive Scalars
ABSTRACT Batchelor predicted that a passive scalar ψν$\psi ^\nu$ with diffusivity ν$\nu$, advected by a smooth fluid velocity, should typically have Fourier mass distributed as |ψ̂ν|2(k)≈|k|−d$|\widehat{\psi }^\nu |^2(k) \approx |k|^{-d}$ for |k|≪ν−1/2$|k| \ll \nu ^{-1/2}$.
William Cooperman, Keefer Rowan
wiley +1 more source
Personalized Differential Privacy for Ridge Regression Under Output Perturbation
ABSTRACT The increased application of machine learning (ML) in sensitive domains requires protecting the training data through privacy frameworks, such as differential privacy (DP). Traditional DP enforces a uniform privacy level ε$$ \varepsilon $$, which bounds the maximum privacy loss that each data point in the dataset is allowed to incur.
Krishna Acharya +3 more
wiley +1 more source
On the equivalence of Clauser-Horne and Eberhard inequality based tests
Recently, the results of the first experimental test for entangled photons closing the detection loophole (also referred to as the fair sampling loophole) were published (Vienna, 2013).
Basieva, Irina +5 more
core +1 more source
Chebyshev type inequalities by means of copulas [PDF]
A copula is a function which joins (or 'couples') a bivariate distribution function to its marginal (one-dimensional) distribution functions. In this paper, we obtain Chebyshev type inequalities by utilising copulas.
Dragomir, Sever S., Kikianty, Eder
openaire +4 more sources
ABSTRACT Binary search trees (BSTs) are fundamental data structures whose performance is largely governed by tree height. We introduce a block model for constructing BSTs by embedding internal BSTs into the nodes of an external BST—a structure motivated by parallel data architectures—corresponding to composite permutations formed via Kronecker or ...
John Peca‐Medlin, Chenyang Zhong
wiley +1 more source
A Review of the Chebyshev Inequality Pertaining to Fractional Integrals
In this article, we give a brief review of a well-known integral inequality that gives information about the integral of the product of two functions using synchronous functions, the Chebyshev inequality.
Péter Kórus +1 more
doaj +1 more source

