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18: Wahrscheinlichkeitstheorie, Vorlesung, SS 2016, am 11.07.2016

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18 | 0:00:00 Starten 0:00:10 Englische Zusammenfassung wichtiger Begriffe und Resultate von Lektion 17 0:04:14 Diskussion (Filtration, Adaptiertheit, Stoppzeit) 0:10:19 Charakterisierung einer Stoppzeit 0:13:35 Summen, Maxima und Minima von Stoppzeiten sind Stoppzeiten 0:15:09 Beispiele für Stoppzeiten (Ersteintrittszeiten, konstante Stoppzeit) 0:21:24 Sigma-Algebra der tau-Vergangenheit 0:24:57 Satz (Messbarkeit einer gestoppten Zufallsvariablen) 0:30:10 Beispiel (Stoppen in einem Urnenmodell) 0:40:59 Submartingal, Supermartingal, Martingal 0:45:35 Interpretation (Submartingal, Supermartingal, Martingal) 0:49:00 Monotonie bzw, Konstanz der Folge (E(X_n)) bei Sub- bzw. Supermartingal und Martingal 0:51:43 Test eines Sub- bzw. Supermartingals auf ein Martingal 0:55:25 Beispiel: Partialsummen unabhängiger Zufallsvariablen 0:59:43 Beispiel: (Partial-)Produkte unabhängiger Zufallsvariablen 1:03:30 Das Doobsche Martingal 1:07:26 Prävisible (vorhersagbare) Folge 1:09:49 Beispiel 1:11:27 Ein vorhersagbares Martingal ist mit Wahrscheinlichkeit 1 konstant 1:13:35 Die Doob-Zerlegung
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Content provided by Karlsruher Institut für Technologie (KIT). All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Karlsruher Institut für Technologie (KIT) or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ro.player.fm/legal.
18 | 0:00:00 Starten 0:00:10 Englische Zusammenfassung wichtiger Begriffe und Resultate von Lektion 17 0:04:14 Diskussion (Filtration, Adaptiertheit, Stoppzeit) 0:10:19 Charakterisierung einer Stoppzeit 0:13:35 Summen, Maxima und Minima von Stoppzeiten sind Stoppzeiten 0:15:09 Beispiele für Stoppzeiten (Ersteintrittszeiten, konstante Stoppzeit) 0:21:24 Sigma-Algebra der tau-Vergangenheit 0:24:57 Satz (Messbarkeit einer gestoppten Zufallsvariablen) 0:30:10 Beispiel (Stoppen in einem Urnenmodell) 0:40:59 Submartingal, Supermartingal, Martingal 0:45:35 Interpretation (Submartingal, Supermartingal, Martingal) 0:49:00 Monotonie bzw, Konstanz der Folge (E(X_n)) bei Sub- bzw. Supermartingal und Martingal 0:51:43 Test eines Sub- bzw. Supermartingals auf ein Martingal 0:55:25 Beispiel: Partialsummen unabhängiger Zufallsvariablen 0:59:43 Beispiel: (Partial-)Produkte unabhängiger Zufallsvariablen 1:03:30 Das Doobsche Martingal 1:07:26 Prävisible (vorhersagbare) Folge 1:09:49 Beispiel 1:11:27 Ein vorhersagbares Martingal ist mit Wahrscheinlichkeit 1 konstant 1:13:35 Die Doob-Zerlegung
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