Spatio-temporal analysis of dependent risk with an application to cyberattacks data
From MaRDI portal
Publication:6665541
DOI10.1214/24-aoas1952MaRDI QIDQ6665541
Chae Young Lim, Yeonwoo Rho, Songhyun Kim
Publication date: 17 January 2025
Published in: The Annals of Applied Statistics (Search for Journal in Brave)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A Mathematical Theory of Communication
- Testing the null hypothesis of stationarity against the alternative of a unit root. How sure are we that economic time series have a unit root?
- Estimating the dimension of a model
- Interpolation of spatial data. Some theory for kriging
- Inference from iterative simulation using multiple sequences
- Copula approaches for modeling cross-sectional dependence of data breach losses
- Generalized autoregressive conditional heteroscedasticity
- Stochastic properties of spatial and spatiotemporal ARCH models
- Efficient simulation and integrated likelihood estimation in state space models
- Distribution of the Estimators for Autoregressive Time Series With a Unit Root
- Geostatistics
- Testing for unit roots in autoregressive-moving average models of unknown order
- On Fractionally Integrated Autoregressive Moving-Average Time Series Models With Conditional Heteroscedasticity
- Modeling multivariate cybersecurity risks
- A Stationary Spatio‐Temporal GARCH Model
- Fractionally integrated GARCH model with tempered stable distribution: a simulation study
- Equation of State Calculations by Fast Computing Machines
- Statistics for Spatial Data
- Monte Carlo sampling methods using Markov chains and their applications
- Modeling multivariate cyber risks: deep learning dating extreme value theory
- The Elements of Statistical Learning
This page was built for publication: Spatio-temporal analysis of dependent risk with an application to cyberattacks data