PRIZES to win! PROMOTIONS

Close Notification

Your cart does not contain any items

Random Variables and Probability Distributions

H. Cramer (Stockholms Universitet) B. Bollobas W. Fulton A. Katok

$137.95   $110.14

Paperback

Not in-store but you can order this
How long will it take?

QTY:

English
Cambridge University Press
03 June 2004
This tract develops the purely mathematical side of the theory of probability, without reference to any applications. When originally published, it was one of the earliest works in the field built on the axiomatic foundations introduced by A. Kolmogoroff in his book Grundbegriffe der Wahrscheinlichkeitsrechnung, thus treating the subject as a branch of the theory of completely additive set functions. The author restricts himself to a consideration of probability distributions in spaces of a finite number of dimensions, and to problems connected with the Central Limit Theorem and some of its generalizations and modifications. In this edition the chapter on Liapounoff's theorem has been partly rewritten, and now includes a proof of the important inequality due to Berry and Esseen. The terminology has been modernized, and several minor changes have been made.
By:  
Series edited by:   , , ,
Imprint:   Cambridge University Press
Country of Publication:   United Kingdom
Volume:   36
Dimensions:   Height: 216mm,  Width: 140mm,  Spine: 8mm
Weight:   180g
ISBN:   9780521604864
ISBN 10:   0521604869
Series:   Cambridge Tracts in Mathematics
Pages:   132
Publication Date:  
Audience:   Professional and scholarly ,  Undergraduate
Format:   Paperback
Publisher's Status:   Active
Preface to the first edition; Preface to the second edition; Preface to the third edition; Abbreviations; Part I. Principles: 1. Introductory remarks; 2. Axioms and preliminary theorems; Part II. Distributions in R1: 3. General properties; 4. Characteristic functions; 5. Addition of independent variables; 6. The normal distribution and the central limit theorem; 7. Error estimation; 8. A class of stochastic processes; Part III. Distributions in R2: 9. General properties; 10. The normal distribution and the central limit theorem; Bibliography.

See Also