Advanced Probability Theory, Second Edition,
Numerical Solution of Markov Chains
Point Processes and Their Statistical Inference
Statistical Inference in Stochastic Processes
By Janos Galambos
August 08, 1995
This work thoroughly covers the concepts and main results of probability theory, from its fundamental principles to advanced applications. This edition provides examples early in the text of practical problems such as the safety of a piece of engineering equipment or the inevitability of wrong ...
Edited By William J. Stewart
May 23, 1991
Papers presented at a workshop held January 1990 (location unspecified) cover just about all aspects of solving Markov models numerically. There are papers on matrix generation techniques and generalized stochastic Petri nets; the computation of stationary distributions, including aggregation/disagg...
By Alan Karr
March 01, 1991
Maintaining the excellent features that made the first edition so popular, this outstanding reference/text presents the only comprehensive treatment of the theory of point processes and statistical inference for point processes-highlighting both pointprocesses on the real line and sp;,.tial point ...
Edited By N.U. Prabhu
December 18, 1990
Covering both theory and applications, this collection of eleven contributed papers surveys the role of probabilistic models and statistical techniques in image analysis and processing, develops likelihood methods for inference about parameters that determine the drift and the jump mechanism of a di...
July 17, 1989
This book deals with Markov chains and Markov renewal processes (M/G/1 type). It discusses numerical difficulties which are apparently inherent in the classical analysis of a variety of stochastic models by methods of complex analysis....