We propose a new method, the "Auto-SLEX" method, for analyzing bivariate non-stationary processes. The Auto-SLEX method is a procedure that automatically segments the time series into approximatively stationary blocks and automatically estimates the time-varying spectra and coherence.

This article reviews the role of wavelets in statistical time series analysis. We survey work that emphasises scale such as estimation of variance and the scale exponent of a process with a specific scale behaviour such as 1/f processes. We present some of our own work on locally stationary...

A consistent estimator for the spectral density of a stationary random process can be obtained by smoothing the periodigrams across frequency. An important component of smoothing is the choice of the span. In this paper, we propose a span selector originally developed for use in fitting...