We develop the necessary methodology to conduct principal component analysis at high
frequency. We construct estimators of realized eigenvalues, eigenvectors, and principal …

The detection of (structural) breaks or the so called change point problem has drawn
increasing attention from the theoretical, applied economic and financial fields. Much of the …

Control of the increasing fossil fuel‐based carbon dioxide (CO2) emissions and the
associated environmental consequences are important for sustainable development in …

This article considers the problem of estimating a change point in the covariance matrix in a
sequence of high-dimensional vectors, where the dimension is substantially larger than the …

Evidence of the non stationary behavior of functional connectivity (FC) networks has been
observed in task based functional magnetic resonance imaging (fMRI) experiments and …

This paper assesses the stochastic convergence of relative CO _ 2 CO 2 emissions within
28 OECD countries over the period 1950–2013. Using the local Whittle estimator and some …

To estimate dynamic functional connectivity for functional magnetic resonance imaging
(fMRI) data, two approaches have dominated: sliding window and change point methods …

Functional magnetic resonance imaging (fMRI) time series data presents a unique
opportunity to understand temporal brain connectivity, and models that uncover the complex …

This paper deals with analyzing structural breaks in the covariance operator of sequentially
observed functional data. For this purpose, procedures are developed to segment an …

This paper develops an estimation and testing framework for a stationary large panel model
with observable regressors and unobservable common factors. We allow for slope …