Results 31 to 40 of about 18,342 (121)

Optimal Hedging Strategies in the Low‐Sulphur Bunker Fuel Landscape

open access: yesEuropean Financial Management, EarlyView.
ABSTRACT The IMO2020 regulation for the green transition in shipping turned the industry into using two compliant bunker fuels: very low‐sulphur fuel oil (VLSFO) and low‐sulphur marine gas oil (LSMGO). VLSFO futures contracts introduced in late 2019 and other energy‐related futures contracts indicate that the VLSFO contracts trading on the Singapore ...
Xiwen Bai   +2 more
wiley   +1 more source

A unified framework for solving a general class of conditional and robust set-membership estimation problems

open access: yes, 2014
In this paper we present a unified framework for solving a general class of problems arising in the context of set-membership estimation/identification theory.
Cerone, Vito   +3 more
core   +1 more source

On Spatial Point Processes With Composition‐Valued Marks

open access: yesInternational 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

Projection Estimates of Constrained Functional Parameters [PDF]

open access: yes
AMS classifications: 62G05; 62G07; 62G08; 62G20; 62G32;estimation;convex function;extreme value copula;Pickands dependence function;projection;shape constraint;support function;tangent ...
Fils-Villetard, A.   +2 more
core   +1 more source

A Non‐Parametric Framework for Correlation Functions on Product Metric Spaces

open access: yesInternational Statistical Review, EarlyView.
Summary We propose a non‐parametric framework for analysing data defined over products of metric spaces, a versatile class encountered in various fields. This framework accommodates non‐stationarity and seasonality and is applicable to both local and global domains, such as the Earth's surface, as well as domains evolving over linear time or time ...
Pier Giovanni Bissiri   +3 more
wiley   +1 more source

Relative Entropy Relaxations for Signomial Optimization [PDF]

open access: yes, 2014
Signomial programs (SPs) are optimization problems specified in terms of signomials, which are weighted sums of exponentials composed with linear functionals of a decision variable.
Chandrasekaran, Venkat, Shah, Parikshit
core  

Estimation of a $k$-monotone density: limit distribution theory and the spline connection

open access: yes, 2007
We study the asymptotic behavior of the Maximum Likelihood and Least Squares Estimators of a $k$-monotone density $g_0$ at a fixed point $x_0$ when $k>2$. We find that the $j$th derivative of the estimators at $x_0$ converges at the rate $n^{-(k-j)/(2k+1)
Balabdaoui, Fadoua, Wellner, Jon A.
core   +1 more source

The Accuracy Smoothness Dilemma in Prediction: A Novel Multivariate M‐SSA Forecast Approach

open access: yesJournal of Time Series Analysis, EarlyView.
ABSTRACT Forecasting presents a complex estimation challenge, as it involves balancing multiple, often conflicting, priorities and objectives. Conventional forecast optimization methods typically emphasize a single metric, such as minimizing the mean squared error (MSE), which may neglect other crucial aspects of predictive performance. To address this
Marc Wildi
wiley   +1 more source

Reinforcement Learning for Jump‐Diffusions, With Financial Applications

open access: yesMathematical Finance, EarlyView.
ABSTRACT We study continuous‐time reinforcement learning (RL) for stochastic control in which system dynamics are governed by jump‐diffusion processes. We formulate an entropy‐regularized exploratory control problem with stochastic policies to capture the exploration–exploitation balance essential for RL.
Xuefeng Gao, Lingfei Li, Xun Yu Zhou
wiley   +1 more source

An Overview of Artificial Intelligence and Machine Learning Approaches for Building Energy Analysis, Characterization, Control, and Grid Support Services Provision

open access: yesWIREs Energy and Environment, Volume 15, Issue 2, June 2026.
Artificial Intelligence and Machine Learning Approaches used in Building Energy Analysis, Control, and Provision of Grid Support Services. ABSTRACT Increasing penetrations of variable renewable energy sources like wind and solar photovoltaic (PV) systems are challenging power system stability worldwide.
Jack S. Bryant   +11 more
wiley   +1 more source

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