上下文无关语言的加权随机生成：随机瓮占用模型中的冲突分析
Weighted random generation of context-free languages: Analysis of collisions in random urn occupancy models
摘要：
本工作分析了冗余的组合对象的加权随机生成算法提出的Denise等人。该计划相关联的加权上下文无关文法的终端符号的权重，扩展这个重量定义乘法的话，并提请字的长度$n$与概率成比例的重量。我们调查了$k$字样本内的冗余程度、由$k$字覆盖的总概率的比例（覆盖率）、第一次碰撞的时间（代数）以及完全收集的时间。对于这四个问题，我们使用一个分析瓮类比来推导渐近估计和/或多项式计算的精确形式。我们说明了这些工具，通过分析丁等人介绍的RNA二级结构统计抽样算法。
英文摘要：
The present work analyzes the redundancy of sets of combinatorial objects produced by a weighted random generation algorithm proposed by Denise et al. This scheme associates weights to the terminals symbols of a weighted context-free grammar, extends this weight definition multiplicatively on words, and draws words of length $n$ with probability proportional their weight. We investigate the level of redundancy within a sample of $k$ word, the proportion of the total probability covered by $k$ words (coverage), the time (number of generations) of the first collision, and the time of the full collection. For these four questions, we use an analytic urn analogy to derive asymptotic estimates and/or polynomially computable exact forms. We illustrate these tools by an analysis of an RNA secondary structure statistical sampling algorithm introduced by Ding et al.
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