State-space Methods for Time Series Analysis : Theory, Applications and Software

Casals, Jose; Garcia-hiernaux, Alfredo; Jerez, Miguel; Sotoca, Sonia; Trindade, A. Alexandre

ISBN 10: 0367570580 / ISBN 13: 9780367570583

Edité par Routledge, 2020

A propos de cet article

Unread book in perfect condition.

N° de réf. du vendeur 41473723

Détails bibliographiques

• Titre: State-space Methods for Time Series Analysis : Theory, Applications and Software
• Éditeur: Routledge
• Date de parution: 2020
• Langue: anglais
• ISBN à 10 chiffres: 0367570580
• ISBN à 13 chiffres: 9780367570583
• Reliure: Couverture souple
• État de l'article: As New

A propos de ce titre

Synopsis

Exploring the advantages of the state-space approach, this book presents numerous computational procedures that can be applied to a previously specified linear model in state-space form. It discusses model estimation and signal extraction; describes many procedures to combine, decompose, aggregate, and disaggregate a state-space form; and covers

À propos de l?auteur

Jose Casals is head of global risk management at Bankia. He is also an associate professor of econometrics at Universidad Complutense de Madrid.

Alfredo Garcia-Hiernaux is an associate professor of econometrics at Universidad Complutense de Madrid and a freelance consultant.

Miguel Jerez is an associate professor of econometrics at Universidad Complutense de Madrid and a freelance consultant. He was previously executive vice-president at Caja de Madrid for six years.

Sonia Sotoca is an associate professor of econometrics at Universidad Complutense de Madrid.

Drs. Casals, Garcia-Hiernaux, Jerez, and Sotoca are all engaged in a long-term research project to apply state-space techniques to standard econometric problems. Their common research interests include state-space methods and time series econometrics.

A. Alexandre (Alex) Trindade is a professor of statistics in the Department of Mathematics and Statistics at Texas Tech University and an adjunct professor in the Graduate School of Biomedical Sciences at Texas Tech University Health Sciences Center. His research spans a broad swath of theoretical and computational statistics.