Full Product Details
Author: Sylvia Frühwirth-Schnatter ,
Angela Bitto ,
Gregor Kastner ,
Alexandra Posekany
Publisher: Springer International Publishing AG
Imprint: Springer International Publishing AG
Edition: 2015 ed.
Volume: 126
Dimensions:
Width: 15.50cm
, Height: 1.30cm
, Length: 23.50cm
Weight: 4.359kg
ISBN: 9783319162379
ISBN 10: 3319162373
Pages: 167
Publication Date: 02 June 2015
Audience:
Professional and scholarly
,
Professional & Vocational
Format: Hardback
Publisher's Status: Active
Availability: Manufactured on demand
We will order this item for you from a manufactured on demand supplier.
Author Information
Sylvia Frühwirth-Schnatter is a Professor of Applied Statistics and Econometrics at the Department of Finance, Accounting, and Statistics at the WU Vienna University of Economics and Business, Austria. She received her PhD in Mathematics from the Vienna University of Technology in 1988. She has published in many leading journals in applied statistics and econometrics on topics such as Bayesian inference, finite mixture models, Markov switching models, state space models, and their application in economics, finance, and business. In 2014, she became elected member of the Austrian Academy of Science. Angela Bitto holds a Masters in Mathematics and is currently working on her PhD in Statistics at the Vienna University of Technology. Her research focuses on the Bayesian estimation of sparse time-varying parameter models. Prior to joining the Institute of Statistics and Mathematics at the WU Vienna University of Economics and Business, she worked as a research analyst for the European Central Bank. Gregor Kastner is an Assistant Professor at the WU Vienna University of Economics and Business and a Lecturer at the University of Applied Sciences in Wiener Neustadt, Austria. He holds Masters in Mathematics, Computer Science, Informatics Management, and Physical Education; in 2014 he received his PhD in Mathematics. Gregor researches the Bayesian modeling of economic time series, in particular the efficient estimation of univariate and high-dimensional stochastic volatility models. His work has been published in leading journals in computational statistics and computer software. Alexandra Posekany is an Assistant Professor at the Institute of Statistics and Mathematics, WU Vienna University of Economics and Business, Austria. She holds a PhD in Mathematics from the Vienna University of Technology. Her research includes applications of Bayesian analysis in computational biology and econometrics, as well as the development of algorithms andstatistical methods in Bayesian computing and big data analysis.
