6 papers
Dimension-invariant uniform consistency of the empirical spatial distribution function and its associated spatial depth estimator
Felix Gnettner, Hyemin Yeon, Piotr Kokoszka
We provide a proof that the empirical spatial distribution estimator in as well as the corresponding plug-in estimator of the spatial depth are uniformly -consis…
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…
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…
Monitoring for a Phase Transition in a Time Series of Wigner Matrices
Nina Dörnemann, Piotr Kokoszka, Tim Kutta +1
We develop methodology and theory for the detection of a phase transition in a time-series of high-dimensional random matrices. In the model we study, at each time point \( t = 1,2…
Prokhorov Metric Convergence of the Partial Sum Process for Reconstructed Functional Data
Tim Kutta, Piotr Kokoszka
Motivated by applications in functional data analysis, we study the partial sum process of sparsely observed, random functions. A key novelty of our analysis are bounds for the dis…
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…