Combinatorics of geometrically distributed random variables: Left-to-right maxima
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Publication:1917529
DOI10.1016/0012-365X(95)00141-IzbMath0853.60006MaRDI QIDQ1917529
Publication date: 7 July 1996
Published in: Discrete Mathematics (Search for Journal in Brave)
Related Items
The binomial transform and the analysis of skip lists ⋮ The multiplicity of left-to-right maxima in geometrically distributed words ⋮ The number of distinct values in a geometrically distributed sample ⋮ The Largest Missing Value in a Sample of Geometric Random Variables ⋮ The visibility parameter for words and permutations ⋮ Record statistics in a random composition ⋮ Combinatorics of geometrically distributed random variables: Run statistics ⋮ Consecutive records in geometrically distributed words ⋮ Central limit theorems for the number of records in discrete models ⋮ Value and position of large weak left-to-right maxima for samples of geometrically distributed variables ⋮ Analysis of an optimized search algorithm for skip lists ⋮ Left-to-right maxima in words and multiset permutations ⋮ Asymptotic normality for the number of records from general distributions ⋮ The largest missing value in a composition of an integer ⋮ D?E?K=(1000)8 ⋮ Unnamed Item ⋮ Gap-free compositions and gap-free samples of geometric random variables ⋮ A note on runs of geometrically distributed random variables ⋮ The water capacity of geometrically distributed words ⋮ Alphabetic points in compositions and words ⋮ Asymptotic behavior of permutation records ⋮ Unnamed Item ⋮ Descents following maximal values in samples of geometric random variables
Cites Work
- Probabilistic counting algorithms for data base applications
- Applications of the theory of records in the study of random trees
- Average search and update costs in skip lists
- A limit theory for random skip lists
- Yet another application of a binomial recurrence. Order statistics
- A result in order statistics related to probabilistic counting
- Digital Search Trees Revisited
- How to count quickly and accurately: A unified analysis of probabilistic counting and other related problems
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