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• W3013697652 abstract "We study a discrete-time Markov process $X_ninmathbb{R}^d$, for which the distribution of the future increments depends only on the relative ranking of its components (descending order by value). We endow the process with a rich-get-richer assumption and show that, together with a finite second moments assumption, it is enough to guarantee almost sure convergence of $X_n$ / $n$. We characterize the possible limits if one is free to choose the initial state, and give a condition under which the initial state is irrelevant. Finally, we show how our framework can account for ranking-based Polya urns and can be used to study ranking-algorithms for web interfaces." @default.
• W3013697652 created "2020-04-03" @default.
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• W3013697652 date "2019-10-02" @default.
• W3013697652 modified "2023-09-25" @default.
• W3013697652 title "Ranking-based rich-get-richer processes" @default.
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