45 citations · 260 across the 33 of their papers we have counts for
4 papers · 1 filter
Variable-Projection Sparse Functional Principal Component Analysis: Interpretable Functional Dimensionality Reduction with Applications to Raman Spectral Data
Han Ying Lim, Dharini Pathmanathan, Philipp Otto +1
Functional principal component analysis (FPCA) provides low-rank representations of functional data but generally produces dense components, making it difficult to identify the loc…
Neighbourhood-Based Generalized Dynamic Principal Components for Spatial Functional Data
Dharini Pathmanathan, Teck Xiang Seow, Philipp Otto +1
Regular-grid spatial functional datasets arise naturally in gridded environmental, oceanographic, climate, and remote-sensing applications, where each spatial location is associate…
Learning Volatility Dependence Networks in UK Equity Markets using Penalised Spatiotemporal ARCH Models
Elkanah Nyabuto, Philipp Otto
Spatiotemporal ARCH models capture temporal volatility persistence and cross-sectional dependence but typically require a predefined spatial weight matrix. This is restrictive in f…
Comparative Analysis of Spatiotemporal Volatility Models: An Empirical Study on Financial Network Series
Ariane N. Meli Chrisko, Jessie Li, Philipp Otto +1
Various spatiotemporal and network GARCH models have recently been proposed to capture volatility interactions, such as the transmission of market risk across financial networks. T…