An investigation of the logical foundations of the theory behind Markov random processes, this text explores subprocesses, transition functions, and conditions for boundedness and continuity. Rather than focusing on probability measures individually, the work explores connections between functions. An elementary grasp of the theory of Markov processes is assumed. 1961 edition.
Reprint of the Prentice-Hall, Inc., Englewood Cliffs, New Jersey, 1961 edition.
Probability Theory: A Concise Course by Y. A. Rozanov This clear exposition begins with basic concepts and moves on to combination of events, dependent events and random variables, Bernoulli trials and the De Moivre-Laplace theorem, and more. Includes 150 problems, many with answers.
Introduction to the Theory of Random Processes by I. I. Gikhman, A. V. Skorokhod Rigorous exposition suitable for elementary instruction. Covers measure theory, axiomatization of probability theory, processes with independent increments, Markov processes and limit theorems for random processes, more. Introduction. Bibliography. 1969 edition.
Markov Processes and Potential Theory by Robert M. Blumenthal, Ronald K. Getoor This graduate-level text explores the relationship between Markov processes and potential theory in terms of excessive functions, multiplicative functionals and subprocesses, additive functionals and their potentials, and dual processes. 1968 edition.
