Empirical‐Process Limit Theory and Filter Approximation Bounds for Score‐Driven Time Series Models
Journal of Time Series Analysis, EarlyView.ABSTRACT This article examines the filtering and approximation‐theoretic properties of score‐driven time series models. Under specific Lipschitz‐type and tail conditions, new results are derived, leading to maximal and deviation inequalities for the filtering approximation error using empirical process theory.
Enzo D'Innocenzo
wiley +1 more source
Models for Patch-Based Image Restoration
EURASIP Journal on Image and Video Processing, 2009 We present a supervised learning approach for object-category specific restoration, recognition, and segmentation of images which are blurred using an unknown kernel.
Petrovic Nemanja +3 more
doaj
Testing Distributional Granger Causality With Entropic Optimal Transport
Journal 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
Journal 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
Faster Hamiltonian Monte Carlo by learning leapfrog scale: an offline randomized solution. [PDF]
Stat ComputWu C, Pudlo P, Robert CP, Stoehr J.
europepmc +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
Non-Parametric Mediation Analysis of Non-Markov Illness-Death Model. [PDF]
Stat MedZhuang LS, Yu JC, Huang YT.
europepmc +1 more source
Reinforcement Learning for Jump‐Diffusions, With Financial Applications
Mathematical 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
Convergence Rate of Euler-Maruyama Scheme to the Invariant Probability Measure Under Total Variation Distance for the SDEs. [PDF]
Entropy (Basel)Wang Y, Ye Y.
europepmc +1 more source
Adaptive Importance Sampling Estimation of an Open Economy Model With Fiscal Policy
Oxford Bulletin of Economics and Statistics, EarlyView.ABSTRACT We propose and estimate an open economy general equilibrium model that includes international trade between Canada and the United States. We estimate our model using a new adaptive methodology based on the mixture of student's t$$ t $$ by Importance Sampling weighted Expectation–Maximisation (MitISEM).
Stefano Grassi +2 more
wiley +1 more source