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Titlebook: Random Trees; An Interplay between Michael Drmota Book 2009 Springer-Verlag Vienna 2009 Combinatorics.Graph.Graph theory.Probability.Random

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Planar Graphs,nalysis. From this point of view outerplanar graphs and series-parallel graphs — these are two subclasses of planar graphs that we will study first — are more tree-like than the class of all planar graphs, since the singularity structure of the corresponding generating functions is of square root ty
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Recursive Algorithms and the Contraction Method,the solutions of the subproblems appropriately. If this idea is iteratively (or recursively) applied then one speaks of a . and, moreover, these kinds of algorithms give rise to a (hidden) tree structure.
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Classes of Random Trees,unting problems. In particular we distinguish between rooted and unrooted, plane and non-plane, and labelled and unlabelled trees. It is also possible to modify the counting procedure by putting certain weights on trees, for example, by using the degree distribution.
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Generating Functions,y can be used to encode the distribution of random variables that are related to counting problems and, hence, asymptotic methods can be applied to obtain probabilistic limit theorems like central limit theorems.
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Advanced Tree Counting,las for basic tree classes and asymptotic formulas for simply generated trees and Pólya trees. However, the main goal is to show that certain tree parameters that behave . (in a proper sense) satisfy a central limit theorem in a natural probabilistic setting.
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