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stat.ME2026
Does PCA Work for Rough Functional Data?
Tim Kutta, Nina Dörnemann, Piotr Kokoszka
Functional data analysis is concerned with the analysis of infinite-dimensional data functions. Functional principal component analysis (FPCA) is a key method to obtain finite-dime…
stat.ME2026
Deep learning estimation of the spectral density of functional time series on large domains
Neda Mohammadi, Soham Sarkar, Piotr Kokoszka
We derive an estimator of the spectral density of a functional time series that is the output of a multilayer perceptron neural network. The estimator is motivated by difficulties…
stat.ME2024
Detection of a structural break in intraday volatility pattern
Piotr Kokoszka, Tim Kutta, Neda Mohammadi +2
We develop theory leading to testing procedures for the presence of a change point in the intraday volatility pattern. The new theory is developed in the framework of Functional Da…