Thomas C. M. Lee

TL;DR: This article considers the problem of modeling a class of nonstationary time series using piecewise autoregressive (AR) processes, and the minimum description length principle is applied to compare various segmented AR fits to the data.

TL;DR: The generalized fiducial inference (GFI) as mentioned in this paper generalizes the idea of Fisher's approach by transferring randomness from the data to the parameter space using an inverse of a data-generating equation without the use of Bayes' theorem.

TL;DR: In this paper, an iterative estimation procedure for performing functional principal component analysis is proposed, which aims at functional or longitudinal data where the repeated measurements from the same subject are correlated, and the resulting data after iteration are theoretically shown to be asymptotically equivalent (in probability) to a set of independent data.

TL;DR: In this article, the problem of detecting break points for a nonstation-ary time series is considered, where the time series follows a parametric nonlinear time-series model in which the parameters may change values at fixed times.

TL;DR: A simulation study of several smoothing parameter selection methods, including two so-called risk estimation methods, finds that the popular method, generalized cross-validation, was outperformed by another method, an improved Akaike Information criterion, that shares the same assumptions and computational complexity.