An Overview of Tes Processes and Modeling Methodology

TES (Transform-Expand-Sample) is a versatile methodology for modeling stationary time series with general marginal distributions and a broad range of dependence structures. From the viewpoint of Monte Carlo simulation, TES constitutes a new and flexible input analysis approach whose principal merit is its potential ability to simultaneously capture first-order and second-order statistics of empirical time series. That is, TES is designed to fit an arbitrary empirical marginal distribution (histogram), and to simultaneously approximate the leading empirical autocorrelations. This paper is a tutorial introduction to the theory of TES processes and to the modeling methodology based on it. It employs a didactic approach which relies heavily on visual intuition as a means of conveying key ideas and an aid in building deep understanding of TES. This approach is in line with practical TES modeling which itself is based on visual interaction under software support. The interaction takes on the form of a heuristic search in a large parameter space, and it currently relies on visual feedback supplied by computer graphics. The tutorial is structured around an illustrative example both to clarify the modeling methodology and to exemplify its efficacy.