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Activity Number:
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444
- Recent Advances in Statistical Methodology for Big Data
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Type:
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Contributed
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Date/Time:
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Thursday, August 12, 2021 : 4:00 PM to 5:50 PM
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Sponsor:
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International Statistical Institute
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Abstract #318935
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Title:
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Weak Convergence of Reversed Martingales to Mixtures of Brownian Motions
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Author(s):
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Mohamed Amezziane* and Ibrahim Ahmad
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Companies:
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Central Michigan University and Oklahoma State University
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Keywords:
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Brownian motion;
Gaussian mixture;
Reversed martingale;
Weak convergence
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Abstract:
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In this work, a weak convergence theorem of random functions of reversed martingale arrays to mixtures of Brownian motions is proved. As a corollary, the convergence of reversed martingale arrays to mixtures of normal distributions is obtained. The main assumption is that the sums of squares in each row converge in probability to a positive random variable independent of the standard Brownian motion.
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Authors who are presenting talks have a * after their name.
