Introduction to State Space Time Series Analysis, Hardcover

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 introduces time series analysis using state space methodology to readers who are neither familiar with time series analysis, nor with state space methods.

Jacques J.F. Commandeur is Senior Researcher at the SWOV Institute for Road Safety Research, Leidschendam, The Netherlands. His Ph.D. is from the Department of Psychometrics and Research Methodology of Leiden University. Between 1991 and 2000 he did research for the Department of Data Theory and the Department of Educational Sciences at Leiden University in the fields of multidimensional scaling and nonlinear multivariate data analysis. Since 2000 he has been at SWOV researching the statistical and methodological aspects of road safety research in general, and time series analysis of developments in road safety in particular.

His research interests are Procrustes analysis; Multidimensional scaling; Distance-based multivariate analysis; Statistical analysis of time series; Forecasting. He has published in international journals in psychometrics and chemometrics. Siem Jan Koopman is Professor of Econometrics at the Free University Amsterdam and the Tinbergen Institute. His Ph.D. is from the London School of Economics (LSE) and he has held positions at the LSE between 1992 and 1997 and at the CentER (Tilburg University) between 1997 and 1999. In 2002 he visited the US Bureau of the Census in Washington DC as an ASA / NSF / US Census / BLS Research Fellow.

His research interests are Statistical analysis of time series; Theoretical and applied time series econometrics; Financial econometrics; Simulation methods; Kalman filtering and smoothing; Forecasting. He has published in many international journals in statistics and econometrics.