A time series is a collection of observations ordered following a parameter that for us is time. Examples occur in a variety of fields (economics, engeneering, meteorology and so on...). For instance, economic time series include share prices on successive days, export totals in successive months, average incomes in successive months, company profits in successive years (see the graph below). M...

Much of what is known about physiological systems has been learned using linear system theory. However, many biomedical signals are apparently random or aperiodic in time. Traditionally, the randomness in biological signals has been ascribed to noise or interactions between very large numbers of constituent components. One of the most important mathematical discoveries of the past few decades i...

The purpose of our article is to provide a summary of a selection of some of the high-quality published computational time series research using R. A more complete overview of time series software available in R for time series analysis is available in the CRAN task views. If you are not already an R user, this article may help you in learning about the R phenomenon and motivate you to learn ho...

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 speci c scale behaviour such as 1/f processes. We present some of our own work on locally stationary wavelet (lsw) processes which model both stationary and some kinds of non-stationary processes. Analysis o...

I introduce feature-based time-series analysis. The time series as a data type is first described, along with an overview of the interdisciplinary time-series analysis literature. I then summarize the range of featurebased representations for time series that have been developed to aid interpretable insights into time-series datasets. Particular emphasis is given to emerging research that facil...

This book is the most comprehensive and clear text for learning dynamics and many related topics of fractals and complexity that I have encountered. I t is appropriate for both classroom use, and for scientists working in a wide variety of fields. The emphasis is on concepts and applications rather than proofs and derivations. I t is ' hands-on' , with practical exercises and a programming proj...