Statistical Analysis of Counting Processes: Lecture Notes in Statistics: Vol 012

Jacobsen, Martin

ISBN 10: 0387907696 / ISBN 13: 9780387907697

Published by Springer Verlag, 1983

About this Item

1st edition. 236 pages. 9.25x6.10x0.54 inches. In Stock.

Seller Inventory # x-0387907696

Bibliographic Details

• Title: Statistical Analysis of Counting Processes: Lecture Notes in Statistics: Vol 012
• Publisher: Springer Verlag
• Publication Date: 1983
• Language: English
• ISBN 10: 0387907696
• ISBN 13: 9780387907697
• Binding: Paperback
• Condition: Brand New
• Weight: 0.37 kilograms

About this title

Synopsis

A first version of these lecture notes was prepared for a course given in 1980 at the University of Copenhagen to a class of graduate students in mathematical statistics. A thorough revision has led to the result presented here. The main topic of the notes is the theory of multiplicative intens­ ity models for counting processes, first introduced by Odd Aalen in his Ph.D. thesis from Berkeley 1975, and in a subsequent fundamental paper in the Annals of Statistics 1978. In Copenhagen the interest in statistics on counting processes was sparked by a visit by Odd Aalen in 1976. At present the activities here are centered around Niels Keiding and his group at the Statistical Re­ search Unit. The Aalen theory is a fine example of how advanced probability theory may be used to develop a povlerful, and for applications very re­ levant, statistical technique. Aalen's work relies quite heavily on the 'theorie generale des processus' developed primarily by the French school of probability the­ ory. But the general theory aims at much more general and profound re­ sults, than what is required to deal with objects of such a relatively simple structure as counting processes on the line. Since also this process theory is virtually inaccessible to non-probabilists, it would appear useful to have an account of what Aalen has done, that includes exactly the amount of probability required to deal satisfactorily and rigorously with statistical models for counting processes.