Results 31 to 40 of about 580 (184)
Restricted Tweedie stochastic block models
Canadian Journal of Statistics, EarlyView.Abstract The stochastic block model (SBM) is a widely used framework for community detection in networks, where the network structure is typically represented by an adjacency matrix. However, conventional SBMs are not directly applicable to an adjacency matrix that consists of nonnegative zero‐inflated continuous edge weights.
Jie Jian, Mu Zhu, Peijun Sang
wiley +1 more source
Pointwise Multipliers of Triebel-Lizorkin Spaces on Carnot-Carathéodory Spaces [PDF]
Journal of Function Spaces and Applications, 2012 Summary: Let \((\mathcal X, d, \mu)\) be a Carnot-Carathéodory space, namely, \(\mathcal X\) is a smooth manifold, \(d\) is a control, or Carnot-Carathéodory, metric induced by a collection of vector fields of finite type. \(\mu\) is a nonnegative Borel regular measure on \(\mathcal X\) satisfying that there exists a constant \(C_0 \in [1, \infty ...
Yanchang Han, Fang Wang
openaire +3 more sources
Nonlinear Response‐History Analyses of Masonry and Mixed Structures With HybriDFEM
Earthquake Engineering &Structural Dynamics, EarlyView.ABSTRACT The hybrid discrete‐finite element (HybriDFEM) method, previously developed to perform static and modal analysis in discrete and coupled discrete‐finite element models, is extended to nonlinear response‐history analyses. The equations of motion for the HybriDFEM model are solved through various numerical time‐integration schemes, both explicit
Igor Bouckaert +2 more
wiley +1 more source
Three‐Dimensional Analytical Model of a Free‐Standing Square Rocking Column
Earthquake Engineering &Structural Dynamics, EarlyView.ABSTRACT A three‐dimensional analytical two‐degree‐of‐freedom (2DOF) model is developed to describe the bounded rocking response of free‐standing rigid square columns subjected to bidirectional seismic excitation. The formulation extends Housner's classical planar theory by deriving the full three‐dimensional equations of motion for a column ...
Dimitra Adamopoulou +1 more
wiley +1 more source
Energy Science &Engineering, EarlyView.An AI‐driven CNN–LSTM forecasting framework is integrated with HOMER Pro to optimally design a grid‐connected PV–wind–BESS microgrid for a rural school in Bangladesh, achieving 91.7% renewable penetration, low energy cost (0.0397 USD/kWh), and an 81.5% reduction in CO2 emissions. ABSTRACT Hybrid renewable microgrid planning in HOMER Pro often relies on
Robiul Khan +5 more
wiley +1 more source
Pointwise multipliers for Campanato spaces on Gauss measure spaces [PDF]
Nagoya Mathematical Journal, 2014 Abstract In this paper, the authors characterize pointwise multipliers for Campanato spaces on the Gauss measure space (ℝ n ,| · |,γ), which includes BMO(γ) as a special case. As applications, several examples of the pointwise multipliers are given. Also, the authors give an example of a nonnegative function in BMO(γ) but not in BLO(γ).
Liu, Liguang, Yang, Dachun
openaire +2 more sources
A Deep Learning Framework for Forecasting Medium‐Term Covariance in Multiasset Portfolios
Journal of Forecasting, EarlyView.ABSTRACT Forecasting the covariance matrix of asset returns is central to portfolio construction, risk management, and asset pricing. However, most existing models struggle at medium‐term horizons, several weeks to months, where shifting market regimes and slower dynamics prevail.
Pedro Reis, Ana Paula Serra, João Gama
wiley +1 more source
Pointwise multipliers between weighted copson and cesàro function spaces
Mathematica Slovaca, 2019 Abstract In this paper the solution of the pointwise multiplier problem between weighted Copson function spaces Copp1,q1(u1, v1) and weighted Cesàro function spaces Cesp2,q2(u2, v2) is presented, where p1, p2, q1, q2 ∈ (0, ∞), p2 ≤ q2 and u1, u2, v1, v2 are weights on (0, ∞).
Gogatishvili, Amiran +2 more
openaire +4 more sources
Journal of Forecasting, EarlyView.ABSTRACT This paper presents a new hybrid model for predicting German electricity prices. The algorithm is based on a combination of Gaussian process regression (GPR) and support vector regression (SVR). Although GPR is a competent model for learning stochastic patterns within data and for interpolation, its performance for out‐of‐sample data is not ...
Abhinav Das +2 more
wiley +1 more source
Intraday Functional PCA Forecasting of Cryptocurrency Returns
Journal of Forecasting, EarlyView.ABSTRACT We study the functional PCA (FPCA) forecasting method in application to functions of intraday returns on Bitcoin. We show that improved interval forecasts of future return functions are obtained when the conditional heteroscedasticity of return functions is taken into account.
Joann Jasiak, Cheng Zhong
wiley +1 more source