The transition and autocorrelation structure of tes processes

Abstract

TES (Transform-Expand-Sample) is a versatile class of stochastic sequences which can capture arbitrary marginals and a wide variety of sample path behavior and autocorrelation functions. In TES, the initial variate is uniform on [0,1) and the next variate is obtained recursively by taking the fractional part (i.e., modulo-1 reduction) of a linear autoregressive scheme. The uniform TES variates can then be further transformed to have arbitrary marginals. A companion paper (Part I) presented the general theory of TES processes. This paper (Part II) contains various examples which demonstrate the efficacy of the TES paradigm by comparing numerical and simulation-based calculations for a variety of TES autocorrelation functions. The results have applications to the modeling of autocorrelated sequences, particularly in a Monte Carlo simulation context.