| Ancillarity-sufficiency interweaving strategy (ASIS) for boosting MCMC estimation of stochastic volatility models G Kastner, S Frühwirth-Schnatter Computational Statistics & Data Analysis 76, 408-423, 2014 | 381 | 2014 |
| Dealing with Stochastic Volatility in Time Series Using the R Package stochvol G Kastner Journal of Statistical Software 69 (5), 1-30, 2016 | 229 | 2016 |
| Efficient Bayesian inference for multivariate factor stochastic volatility models G Kastner, S Frühwirth-Schnatter, HF Lopes Journal of Computational and Graphical Statistics 26 (4), 905-917, 2017 | 145 | 2017 |
| Sparse Bayesian time-varying covariance estimation in many dimensions G Kastner Journal of Econometrics 210 (1), 98-115, 2019 | 119 | 2019 |
| Sparse Bayesian vector autoregressions in huge dimensions G Kastner, F Huber Journal of Forecasting 39 (7), 1142-1165, 2020 | 95 | 2020 |
| Modeling univariate and multivariate stochastic volatility in R with stochvol and factorstochvol D Hosszejni, G Kastner Journal of Statistical Software 100 (12), 1-34, 2021 | 83* | 2021 |
| Should I stay or should I go? A latent threshold approach to large-scale mixture innovation models F Huber, G Kastner, M Feldkircher Journal of Applied Econometrics 34 (5), 621-640, 2019 | 53 | 2019 |
| R Package stochvol: Efficient Bayesian inference for stochastic volatility (SV) models G Kastner, D Hosszejni | 39* | 2019 |
| Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian vector autoregressions? M Feldkircher, L Gruber, F Huber, G Kastner Journal of Forecasting, 2024 | 18* | 2024 |
| Approaches toward the Bayesian estimation of the stochastic volatility model with leverage D Hosszejni, G Kastner Bayesian Statistics and New Generations: BAYSM 2018, Warwick, UK, July 2-3 …, 2019 | 17 | 2019 |
| Heavy-Tailed Innovations in the R Package stochvol G Kastner http://cran.r-project.org/web/packages/stochvol/vignettes/heavytails.pdf, 2015 | 16 | 2015 |
| European rapeseed and fossil diesel: Threshold cointegration analysis and possible implications M Ziegelback, G Kastner Unternehmerische Landwirtschaft zwischen Marktanforderungen und …, 2012 | 16 | 2012 |
| Investigating the Dark Figure of COVID-19 Cases in Austria: Borrowing From the Decode Genetics Study in Iceland R Hirk, G Kastner, L Vana Austrian Journal of Statistics 49 (4), 1-17, 2020 | 12 | 2020 |
| Analysis of Exchange Rates via Multivariate Bayesian Factor Stochastic Volatility Models G Kastner, S Frühwirth-Schnatter, HF Lopes The Contribution of Young Researchers to Bayesian Statistics, Springer …, 2014 | 11 | 2014 |
| Forecasting macroeconomic data with Bayesian VARs: Sparse or dense? It depends! L Gruber, G Kastner arXiv preprint arXiv:2206.04902, 2022 | 7 | 2022 |
| Bayesian modeling and clustering for spatio-temporal areal data: An application to Italian unemployment A Mozdzen, A Cremaschi, A Cadonna, A Guglielmi, G Kastner Spatial Statistics 52, 100715, 2022 | 6 | 2022 |
| On the joint volatility dynamics in international dairy commodity markets AN Rezitis, G Kastner Australian Journal of Agricultural and Resource Economics 65 (3), 704-728, 2021 | 4 | 2021 |
| Arbitrage hedging in markets for the US lean hogs and the EU live pigs M Ziegelbäck, G Kastner Agricultural Economics 59, 505-511, 2013 | 4 | 2013 |
| Package “mfbvar.” S Ankargren, Y Yang, G Kastner | 3 | 2021 |
| Posterior predictive model checking using formal methods in a spatio-temporal model L Vana, E Visconti, L Nenzi, A Cadonna, G Kastner arXiv preprint arXiv:2110.01360, 2021 | 2 | 2021 |
Sylvia Frühwirth-SchnatterProfessor of Applied Statistics and Econometrics, WU Vienna University of Economics and Business在 wu.ac.at 的电子邮件经过验证
