Montag, 10. Januar 2022, 16:45 - 17:45 iCal

ISOR Colloquium

"Posterior predictive model checking using formal methods in a spatio-temporal model"

Speaker: Gregor Kastner (Alpen-Adria-University Klagenfurt)

Online only
Oskar-Morgenstern-Platz 1, 1090 Wien


We propose an interdisciplinary framework, Bayesian formal predictive model checking (Bayes FPMC), which combines Bayesian predictive inference, a well established tool in statistics, with formal verification methods rooting in the computer science community.

Bayesian predictive inference allows for coherently incorporating uncertainty about unknown quantities by making use of methods or models that produce predictive distributions which in turn inform decision problems. By formalizing these problems and the corresponding properties, we can use spatio-temporal reach and escape logic to probabilistically assess their satisfaction. This way, competing models can directly be ranked according to how well they solve the actual problem at hand.

The approach is illustrated on an urban mobility application, where the crowdedness in the center of Milan is proxied by aggregated mobile phone traffic data. We specify several desirable spatio-temporal properties related to city crowdedness such as a fault tolerant network or the reachability of hospitals. After verifying these properties on draws from the posterior predictive distributions, we compare several spatio-temporal Bayesian models based on their overall and property-based predictive performance.

Link to the preprint:


To participate please join our ZOOM Meeting:

Meeting room opens at: January 10, 2021 4.30 pm Vienna

Meeting ID: 961 5811 1761

Password: 294736

Zur Webseite der Veranstaltung


Institut für Statistik und Operations Research


Sabine Sobotka-Tompits, BA
Fakultät für Wirtschaftswissenschaften
Institut für Statistik und Operations Research
+43 1 4277 38631