Abstract

The Bernoulli sieve is the infinite “balls-in-boxes” occupancy scheme with random frequencies Pk=W1⋯Wk−1(1−Wk), where (Wk)k∈N are independent copies of a random variable W taking values in (0,1). Assuming that the number of balls equals n, let Ln denote the number of empty boxes within the occupancy range. In this paper, we investigate convergence in distribution of Ln in the two cases which remained open after the previous studies. In particular, provided that E|logW|=E|log(1−W)|=∞ and that the law of W assigns comparable masses to the neighborhoods of 0 and 1, it is shown that Ln weakly converges to a geometric law. This result is derived as a corollary to a more general assertion concerning the number of zero decrements of nonincreasing Markov chains. In the case that E|logW|<∞ and E|log(1−W)|=∞, we derive several further possible modes of convergence in distribution of Ln. It turns out that the class of possible limiting laws for Ln, properly normalized and centered, includes normal laws and spectrally negative stable laws with finite mean. While investigating the second problem, we develop some general results concerning the weak convergence of renewal shot-noise processes. This allows us to answer a question asked by Mikosch and Resnick (2006) [18].

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.