Results 71 to 80 of about 82,244 (222)
A Bernstein type inequality associated with wavelet bi-frame decomposition
Journal of Inequalities and Applications, 2016 Bernstein inequality is an essential inequality for Besov spaces. Smoothness based approaches are widely used in establishing the inequality. Yet, despite numerous studies over the last two decades, there is still little research focusing on decay-based ...
Kai-Cheng Wang +3 more
doaj +1 more source
On Spatial Point Processes With Composition‐Valued Marks
International Statistical Review, EarlyView.Summary Methods for marked spatial point processes with scalar marks have seen extensive development in recent years. While the impressive progress in data collection and storage capacities has yielded an immense increase in spatial point process data with highly challenging non‐scalar marks, methods for their analysis are not equally well developed ...
Matthias Eckardt +2 more
wiley +1 more source
Change Point Analysis for Functional Data Using Empirical Characteristic Functionals
Journal of Time Series Analysis, EarlyView.ABSTRACT We develop a new method to detect change points in the distribution of functional data based on integrated CUSUM processes of empirical characteristic functionals. Asymptotic results are presented under conditions allowing for low‐order moments and serial dependence in the data establishing the limiting null‐distribution of the proposed test ...
Lajos Horváth +2 more
wiley +1 more source
Estimates for Parameter Littlewood-Paley gκ⁎ Functions on Nonhomogeneous Metric Measure Spaces
Journal of Function Spaces, 2016 Let (X,d,μ) be a metric measure space which satisfies the geometrically doubling measure and the upper doubling measure conditions. In this paper, the authors prove that, under the assumption that the kernel of Mκ⁎ satisfies a certain Hörmander-type ...
Guanghui Lu, Shuangping Tao
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A New Approach to Statistical Inference for Functional Time Series
Journal of Time Series Analysis, EarlyView.ABSTRACT The analysis of time‐indexed functional data plays an important role in the field of business and economic statistics. In the literature, statistical inference for functional time series often involves reducing the dimension of functional data to a finite dimension K$$ K $$, followed by the use of tools from multivariate analysis.
Hanjia Gao, Yi Zhang, Xiaofeng Shao
wiley +1 more source
Measure‐valued processes for energy markets
Mathematical Finance, Volume 35, Issue 2, Page 520-566, April 2025.Abstract We introduce a framework that allows to employ (non‐negative) measure‐valued processes for energy market modeling, in particular for electricity and gas futures. Interpreting the process' spatial structure as time to maturity, we show how the Heath–Jarrow–Morton approach can be translated to this framework, thus guaranteeing arbitrage free ...
Christa Cuchiero +3 more
wiley +1 more source
Approximation by Zygmund means in variable exponent Lebesque spaces [PDF]
Mathematica Moravica, 2019 In the present work we investigate the approximation of the functions by the Zygmund means in variable exponent Lebesgue spaces. Here the estimate which is obtained depends on sequence of the best approximation in Lebesgue spaces with variable exponent ...
Jafarov Sadulla Z.
doaj
Macroscopic Market Making Games
Mathematical Finance, EarlyView.ABSTRACT Building on the macroscopic market making framework as a control problem, this paper investigates its extension to stochastic games. In the context of price competition, each agent is benchmarked against the best quote offered by the others. We begin with the linear case.
Ivan Guo, Shijia Jin
wiley +1 more source
A Refined Well-Posedness Result for the Modified KdV Equation in the Fourier-Lebesgue Spaces. [PDF]
J Dyn Differ Equ, 2023 Chapouto A.
europepmc +1 more source
Cpmposed Grand Lebesgue Spaces
, 2011 In this article we introduce and investigate a new class of rearrangement invariant (r.i.) Banach function spaces, so-called Composed Grand Lebesgue Spaces (CGLS), in particular, Integral Grand Lebesgue Spaces (IGLS), which are some generalizations of known Grand Lebesgue Spaces (GLS). We consider the fundamental functions of CGLS, calculate its Boyd's
Ostrovsky, E., Sirota, L.
openaire +2 more sources