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Limit laws are proven by the contraction method for random vectors of a recursive nature as they arise as parameters of combinatorial structures such as random trees or recursive algorithms, where we use the Zolotarev metric. In comparison to previous applications of this method, a general transfer theorem is derived which allows us to establish a limit law… (More)

- Hsien-Kuei Hwang, Ralph Neininger
- SIAM J. Comput.
- 2002

We characterize all limit laws of the quicksort type random variables defined recursively by X n d = X In + X * n−1−In + T n when the " toll function " T n varies and satisfies general conditions, When the " toll function " T n (cost needed to partition the original problem into smaller subproblems) is small (roughly lim sup n→∞ log E(T n)/ log n ≤ 1/2), X… (More)

- BY MICHAEL MESSER, MARIETTA KIRCHNER, JULIA SCHIEMANN, JOCHEN ROEPER, RALPH NEININGER, GABY SCHNEIDER
- 2014

Nonstationarity of the event rate is a persistent problem in modeling time series of events, such as neuronal spike trains. Motivated by a variety of patterns in neurophysiological spike train recordings, we define a general class of renewal processes. This class is used to test the null hypothesis of stationary rate versus a wide alternative of renewal… (More)

- Ralph Neininger
- Random Struct. Algorithms
- 2001

The contraction method for recursive algorithms is extended to the multivariate analysis of vectors of parameters of recursive structures and algorithms. We prove a general multivariate limit law which also leads to an approach to asymptotic covariances and correlations of the parameters. As an application the asymptotic correlations and a bivariate limit… (More)

- Michael Fuchs, Hsien-Kuei Hwang, Ralph Neininger
- Algorithmica
- 2006

We prove convergence in distribution for the profile (the number of nodes at each level), normalized by its mean, of random recursive trees when the limit ratio ˛ of the level and the logarithm of tree size lies in OE0; e/. Convergence of all moments is shown to hold only for ˛ 2 OE0; 1 (with only convergence of finite moments when ˛ 2 .1; e/). When the… (More)

- Ralph Neininger
- Combinatorics, Probability & Computing
- 2002

The Wiener index is analyzed for random recursive trees and random binary search trees in the uniform probabilistic models. We obtain the expectations, asymptotics for the variances, and limit laws for this parameter. The limit distributions are characterized as the projections of bivariate measures that satisfy certain fixed-point equations. Covariances,… (More)

In the first part of this paper we give an introduction to the contraction method for the analysis of additive recursive sequences of divide and conquer type. Recently some general limit theorems have been obtained by this method based on a general transfer theorem. This allows to conclude from the recursive structure and the asymp-totics of first moment(s)… (More)

- M. MAHMOUD, RALPH NEININGER, George Washington, H. M. MAHMOUD, R. NEININGER
- 2003

We investigate random distances in a random binary search tree. Two types of random distance are considered: the depth of a node randomly selected from the tree, and distance between randomly selected pairs of nodes. By a combination of classical methods and modern contraction techniques we arrive at a Gaussian limit law for normed random distances between… (More)

- Ralph Neininger, Ludger Rüschendorf
- Random Struct. Algorithms
- 1999

It is proved that the internal path length of a d{ dimensional quad tree after normalization converges in distribution. The limiting distribution is characterized as a xed point of a random aane operator. We obtain convergence of all moments and of the Laplace transforms. The moments of the limiting distribution can be evaluated from the recursion and lead… (More)

An algorithm is developed for the exact simulation from distributions that are defined as fixed-points of maps between spaces of probability measures. The fixed-points of the class of maps under consideration include examples of limit distributions of random variables studied in the probabilistic analysis of algorithms. Approximating sequences for the… (More)