Results 101 to 110 of about 4,564 (243)

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

Missing Values in Time Series: A Brief Review and a New Versatile Imputation Method

open access: yesInternational Statistical Review, EarlyView.
Summary Missing data can significantly hamper standard time series analysis, yet they occur frequently in applications. In this paper, we briefly review some available methods for handling missing values and introduce the temporal Wasserstein imputation, a novel method for imputing missing data in time series.
Shuo‐Chieh Huang   +2 more
wiley   +1 more source

Deep reinforcement learning for multi‐restart metaheuristics: an environment design for a hybrid of unbiased exploratory search and covariance matrix adaptation evolution strategy

open access: yesInternational Transactions in Operational Research, EarlyView.
Abstract Multi‐restart metaheuristics can be highly effective for complex optimization problems, yet their performance depends critically on how restarts and algorithmic parameters are selected. This paper introduces a reinforcement learning approach for managing restart‐level decisions and parameter configurations in the UES–CMA‐ES hybrid ...
Antonio Bolufé‐Röhler, Bowen Xu
wiley   +1 more source

Mixing It Up: Inflation at Risk

open access: yesJournal of Money, Credit and Banking, EarlyView.
Abstract Understanding how risk factors shape the economic outlook is essential for guiding policy decisions. This paper develops a flexible framework that decomposes distributional risk forecasts of macro‐economic variables into underlying contributions and supports the construction of interpretable risk measures.
MAXIMILIAN SCHRÖDER
wiley   +1 more source

Brain tissue classification in hyperspectral images using multistage diffusion features and transformer

open access: yesJournal of Microscopy, EarlyView.
Abstract Brain surgery is a widely practised and effective treatment for brain tumours, but accurately identifying and classifying tumour boundaries is crucial to maximise resection and avoid neurological complications. This precision in classification is essential for guiding surgical decisions and subsequent treatment planning.
Neetu Sigger   +2 more
wiley   +1 more source

Testing Distributional Granger Causality With Entropic Optimal Transport

open access: yesJournal of Time Series Analysis, EarlyView.
ABSTRACT We develop a novel nonparametric test for Granger causality in distribution based on entropic optimal transport. Unlike classical mean‐based approaches, the proposed method directly compares the full conditional distributions of a response variable with and without the history of a candidate predictor.
Tao Wang
wiley   +1 more source

On Testing for Independence Between Generalized Error Models of Several Time Series

open access: yesJournal of Time Series Analysis, EarlyView.
ABSTRACT We define generalized innovations associated with generalized error models having arbitrary distributions, that is, distributions that can be mixtures of continuous and discrete distributions. These models include stochastic volatility models and regime‐switching models with possibly zero‐inflated regimes.
Kilani Ghoudi   +2 more
wiley   +1 more source

Measure‐valued processes for energy markets

open access: yesMathematical 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

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

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