This text is devoted to the development of certain probabilistic methods
in the specific field of stochastic differential equations and limit
theorems for Markov processes. Specialists, researchers, and students in
the field of probability will find it a source of important theorems as
well as a remarkable amount of advanced material in compact form.
The treatment begins by introducing the basic facts of the theory of
random processes and constructing the auxiliary apparatus of stochastic
integrals. All proofs are presented in full. Succeeding chapters explore
the theory of stochastic differential equations, permitting the
construction of a broad class of Markov processes on the basis of simple
processes. The final chapters are devoted to various limit theorems
connected with the convergence of a sequence of Markov chains to a
Markov process with continuous time. Topics include the probability
method of estimating how fast the sequence converges in the limit
theorems and the precision of the limit theorems.