Time Series with Long Memory

ISBN-13: 9780199257300 / Angielski / Miękka / 2003 / 392 str.

Robinson

Opis

Long memory processes constitute a broad class of models for stationary and non-stationary time series data in economics, finance and other fields. Their key feature is persistence, with high correlation between events that are remote in time. A single memory parameter economically indexes this persistence, as part of a rich parametric or non-parametric structure for the process. Unit root processes can be covered, along with processes that are stationary, but with stronger persistence than autoregressive moving averages, these latter being included in a broader class which describes both short memory and negative memory.

O autorze

Peter M. Robinson is Tooke Professor of Economic Science and Statistics, and Leverhulme Research Professor at the London School of Economics. He was previously Professor of Econometrics at the same institution. He has served as Co-Editor of Econometrica and the Journal of Econometrics and Econometric Theory, and as Associate Editor of The Annals of Statistics and other journals. He is a Fellow of the British Academy, Fellow of the Institute of Mathematical Statistics, and Fellow of the Econometric Society.