Results 21 to 30 of about 270 (123)
Fast Nodal Hessian Computation for Peridynamic Fracture Simulation
Computer Graphics Forum, EarlyView.A fast, exact nodal Hessian computation for Non‐Ordinary State‐Based Peridynamics is introduced through analytical simplification and a warp‐centric GPU strategy. The method accelerates preconditioned solvers and Vertex Block Descent, enabling interactive fracture simulation with physical accuracy.
Yuxiong Qin +2 more
wiley +1 more source
International Statistical Review, EarlyView.Summary Understanding the spread of infectious diseases such as COVID‐19 is crucial for informed decision‐making and resource allocation. A critical component of disease behaviour is the velocity with which disease spreads, defined as the rate of change between time and space.
Fernando Rodriguez Avellaneda +2 more
wiley +1 more source
Mixing It Up: Inflation at Risk
Journal 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
Sequential Outlier Detection in Nonstationary Time Series
Journal of Time Series Analysis, EarlyView.ABSTRACT A novel method for sequential outlier detection in nonstationary time series is proposed. The method tests the null hypothesis of “no outlier” at each time point, addressing the multiple testing problem by bounding the error probability of successive tests, using extreme‐value theory. The asymptotic properties of the test statistic are studied
Florian Heinrichs +2 more
wiley +1 more source
Mathematical Finance, EarlyView.ABSTRACT This study develops a novel multivariate stochastic framework for assessing systemic risks, such as climate and nature‐related shocks, within production or financial networks. By embedding a linear stochastic fluid network, interpretable as a generalized vector Ornstein–Uhlenbeck process, into the production network of interdependent ...
Giovanni Amici +3 more
wiley +1 more source
On the Exact Limiting Distribution of a Volatility Target Index
Mathematical Finance, EarlyView.ABSTRACT Assuming a lognormal distribution for the underlying risky asset, we study the limiting distribution of a volatility target index as the rebalancing time step approaches zero. Two limit theorems (a strong law of large numbers and a central limit theorem) are established, and as an application, the exact limiting distribution is derived.
Xuan Liu, Michel Gauthier
wiley +1 more source
Assessing the Effectiveness of Workers' Selection Exams: The Case of the Bank of Italy
Oxford Bulletin of Economics and Statistics, EarlyView.ABSTRACT High‐stakes exams can be used to rank and select candidates for job openings, and the ability of those selected hinges on the design of the exam. I propose a method to model candidates' performance to assess how effective the exam is at selecting high‐ability candidates.
Santiago Pereda‐Fernández
wiley +1 more source
Repelled Point Processes With Application to Numerical Integration
Scandinavian Journal of Statistics, EarlyView.ABSTRACT We look at Monte Carlo numerical integration from a stochastic geometry point of view. While crude Monte Carlo estimators relate to linear statistics of a homogeneous Poisson point process (PPP), linear statistics of more regularly spread point processes can yield unbiased estimators with faster‐decaying variance, and thus lower integration ...
Diala Hawat +3 more
wiley +1 more source
Sparse Minimum Redundancy Maximum Relevance for Feature Selection
Scandinavian Journal of Statistics, EarlyView.ABSTRACT We propose a feature screening method that integrates both feature–feature and feature–target relationships. Inactive features are identified via a penalized minimum Redundancy Maximum Relevance (mRMR) procedure, which is the continuous version of the classical mRMR penalized by a non‐convex regularizer, and where the parameters estimated as ...
Peter Naylor +3 more
wiley +1 more source
Bayesian Inference for Multivariate Monotone Densities
Scandinavian Journal of Statistics, EarlyView.ABSTRACT We consider a nonparametric Bayesian approach to estimation and testing for a multivariate monotone density. Instead of following the conventional Bayesian approach of imposing a prior that satisfies the monotonicity restriction, we place a prior on the step heights via binning and a Dirichlet distribution. The resulting posterior distribution
Kang Wang, Subhashis Ghosal
wiley +1 more source