5 papers · 1 filter
A Simple and Robust Multi-Fidelity Data Fusion Method for Effective Modeling of Citizen-Science Air Pollution Data
Camilla Andreozzi, Pietro Colombo, Philipp Otto
We propose a robust multi-fidelity Gaussian process for integrating sparse, high-quality reference monitors with dense but noisy citizen-science sensors. The approach replaces the…
Multivariate Low-Rank State-Space Model with SPDE Approach for High-Dimensional Data
Jacopo Rodeschini, Lorenzo Tedesco, Francesco Finazzi +2
This paper proposes a novel low-rank approximation to the multivariate State-Space Model. The Stochastic Partial Differential Equation (SPDE) approach is applied component-wise to…
A Dynamic Spatiotemporal and Network ARCH Model with Common Factors
Osman Doğan, Raffaele Mattera, Philipp Otto +1
We introduce a dynamic spatiotemporal volatility model that extends traditional approaches by incorporating spatial, temporal, and spatiotemporal spillover effects, along with vola…
A Multivariate Spatial and Spatiotemporal ARCH Model
Philipp Otto
This paper introduces a multivariate spatiotemporal autoregressive conditional heteroscedasticity (ARCH) model based on a vec-representation. The model includes instantaneous spati…
Spatial and Spatiotemporal GARCH Models -- A Unified Approach
Philipp Otto, Wolfgang Schmid
In time-series analyses, particularly for finance, generalized autoregressive conditional heteroscedasticity (GARCH) models are widely applied statistical tools for modelling volat…