This article presents a review of some modern approaches to trend extraction for one-
dimensional time series, which is one of the major tasks of time series analysis. The trend of …

Providing a practical introduction to state space methods as applied to unobserved
components time series models, also known as structural time series models, this book …

This article describes recent developments in software, diagnostics and research for
seasonal adjustment. These include: software merging X-12-ARIMA and SEATS; improved …

In this paper we review the state space approach to time series analysis and establish the
notation that is adopted in this special volume of the Journal of Statistical Software. We first …

The paper provides general matrix formulas for minimum mean squared error signal
extraction for a finitely sampled time series whose signal and noise components are …

Estimation of Stochastic Processes is intended for researchers in the field of econometrics,
financial mathematics, statistics or signal processing. This book gives a deep understanding …

This paper provides analyses of daily retail data, extracting annual and weekly seasonal
patterns along with moving holiday effects, using an unobserved components framework. It …

Real-time signal extraction is about the definition and the estimation of signals at the current
boundary of time series. Accessory, this book is also about the early detection of turning …

Seasonal adjustment methods are used to process and publish thousands of time series
across the world each month, and judgement of the adequacy relies heavily upon seasonal …

Risk is at the centre of many policy decisions in companies, governments and other
institutions. The risk of road fatalities concerns local governments in planning …