Sylvia Frühwirth-Schnatter

Sylvia Frühwirth-Schnatter
Sylvia Frühwirth-Schnatter
Born	May 21, 1959; Vienna, Austria
Nationality	Austrian
Alma mater	TU Wien
Known for	Bayesian inference, Mixture distribution, Markov chain Monte Carlo
	Scientific career
Fields	Statistics
Institutions	Vienna University of Economics and Business
Website	statmath.wu.ac.at/~fruehwirth/

Sylvia Frühwirth-Schnatter (born May 21, 1959) is an Austrian statistician and professor of applied statistics and econometrics at the Vienna University of Economics and Business. She is known for her research in Bayesian analysis and is currently (2020) the President of the International Society for Bayesian Analysis.[1]

Biography

Sylvia Frühwirth-Schnatter was born in 1959 in the Brigittenau district of Vienna. After attaining her doctorate in engineering mathematics from the TU Wien she held numerous academic positions, including professor of statistics at the Johannes Kepler University Linz. Since 2011, she is full professor of statistics at the Vienna University of Economics and Business.[2] Sylvia Frühwirth-Schnatter is married and mother of three sons.

In her research, Sylvia Frühwirth-Schnatter inter alia explores ideas relating to Bayesian econometrics, such as efficient Markov chain Monte Carlo methods and Bayesian analysis of finite Mixture models. In 2014, she co-developed a Bayesian approach to Exploratory Factor Analysis with Nobel Prize winning economist James Heckman.[3] She is a quadruple winner of the WU Best Paper Award[4] and recipient of the DeGroot Prize[5] bestowed by the International Society for Bayesian Analysis for her monograph on Markov switching models.

Frühwirth-Schnatter, S. (2006). Finite mixture and Markov switching models. Springer Science & Business Media. ISBN 978-0-387-35768-3
Conti, G., Frühwirth-Schnatter, S., Heckman, J. J., & Piatek, R. (2014). Bayesian exploratory factor analysis. Journal of econometrics, 183(1), 31–57.
Frühwirth‐Schnatter, S. (1994). Data augmentation and dynamic linear models. Journal of time series analysis, 15(2), 183–202.

gollark: Any specific ones out of those other than just the examples they list?

gollark: Oh, I should have mentioned, 2D square grids (yes, kind of boring, but hexagons are hard).

gollark: Can people recommend some interesting rules to implement in a simple (slow) browser-based CA thingy?

gollark: Hi.

gollark: Did you know? For all epsilon = 0, there exists a delta such that epsilon = delta = 0.

"Leadership". International Society for Bayesian Analysis. Retrieved February 16, 2019.
"Sylvia Frühwirth-Schnatter". Vienna University of Economics and Business. Retrieved February 16, 2019.
Conti, G.; Frühwirth-Schnatter, S.; Heckman, J. J.; Piatek, R. (November 2014). "Bayesian exploratory factor analysis". Journal of Econometrics. 183 (1): 31–57. doi:10.1016/j.jeconom.2014.06.008. PMC 4242469. PMID 25431517.
"WU Best Paper Award". Vienna University of Economics and Business. Retrieved February 16, 2019.
"DeGroot Prize". International Society for Bayesian Analysis. Retrieved February 16, 2019.

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