Thesiss

This dissertation examines the effect of model-selection uncertainty in autoregressive models. The first chapter of the dissertation identifies the effects of model-selection uncertainty in autoregressive models—namely, the bias of the coefficient estimates, the bias of their st…

Fitting multivariate autoregressive (AR) models is fundamental for analysis of time-series data in a wide range of applications in science, engineering, econometrics, signal processing, and data-science. This dissertation considers the problem of learning a p-lag multivariate AR…