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Procesos Estocásticos Discretos (Galager)
7: Caminatas Aleatorias, Grandes Desviaciones y Martingales

7: Caminatas Aleatorias, Grandes Desviaciones y Martingales

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30 oct 2022
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- 6.9: Resumen
- 7.1: Introducción

Robert Gallager
Massachusetts Institute of Technology via MIT OpenCourseWare

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7.1: Introducción
7.3: Detección, Decisiones y Pruebas de Hipótesis
7.4: Probabilidades de cruce de umbrales en caminatas aleatorias
7.5: Umbrales, reglas de detención e identidad de Wald
7.6: Martingales
7.7: Submartingales y Supermartingales
7.8: Detener procesos y detener ensayos
7.9: Las desigualdades de Kolmogorov
Ahora utilizamos los teoremas anteriores para establecer la desigualdad de la submartingala de Kolmogorov, que es un importante fortalecimiento de la desigualdad de Markov. Así como se utilizó la desigualdad de Markov en la Sección 1.7 para derivar la desigualdad de Chebichev y luego la débil ley de grandes números, la desigualdad de la submartingala de Kolmogorov se utilizará para fortalecer la desigualdad Chebichev, de la que seguirá la fuerte ley de grandes números.
7.10: Markov Caminatas Aleatorias Moduladas
7.11: Resumen
7.12: Ejercicios

Miniaturas: http://spiff.rit.edu/classes/phys440/phys440.html

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