Probabilistic methods in combinatorial analysis

This 1997 work explores the role of probabilistic methods for solving combinatorial problems. These methods not only provide the means of efficiently using such notions as characteristic and generating functions, the moment method and so on but also let us use the powerful technique of limit theorem...

Full description

Bibliographic Details
Main Author: Sachkov, Vladimir Nikolaevich
Format: eBook
Language:English
Published: Cambridge Cambridge University Press 1997
Series:Encyclopedia of mathematics and its applications
Subjects:
Online Access:
Collection: Cambridge Books Online - Collection details see MPG.ReNa
LEADER 02158nmm a2200277 u 4500
001 EB001383058
003 EBX01000000000000000906023
005 00000000000000.0
007 cr|||||||||||||||||||||
008 170324 ||| eng
020 |a 9780511666193 
050 4 |a QA164 
100 1 |a Sachkov, Vladimir Nikolaevich 
130 0 |a Veroi͡atnostnye metody v kombinatornom analize 
245 0 0 |a Probabilistic methods in combinatorial analysis  |c Vladimir N. Sachkov 
260 |a Cambridge  |b Cambridge University Press  |c 1997 
300 |a x, 246 pages  |b digital 
505 0 |a 1. Relevant elements of probability theory -- 2. Combinatorial properties of random nonnegative matrices -- 3. Probabilistic problems in the general combinatorial scheme -- 4. Random partitions of sets -- 5. Random permutations -- 6. Random graphs and random mappings 
653 |a Combinatorial analysis 
653 |a Probabilities 
041 0 7 |a eng  |2 ISO 639-2 
989 |b CBO  |a Cambridge Books Online 
490 0 |a Encyclopedia of mathematics and its applications 
856 4 0 |u https://doi.org/10.1017/CBO9780511666193  |x Verlag  |3 Volltext 
082 0 |a 519.2 
520 |a This 1997 work explores the role of probabilistic methods for solving combinatorial problems. These methods not only provide the means of efficiently using such notions as characteristic and generating functions, the moment method and so on but also let us use the powerful technique of limit theorems. The basic objects under investigation are nonnegative matrices, partitions and mappings of finite sets, with special emphasis on permutations and graphs, and equivalence classes specified on sequences of finite length consisting of elements of partially ordered sets; these specify the probabilistic setting of Sachkov's general combinatorial scheme. The author pays special attention to using probabilistic methods to obtain asymptotic formulae that are difficult to derive using combinatorial methods. This was an important book, describing many ideas not previously available in English; the author has taken the chance to rewrite parts of the text and refresh the references where appropriate