Nonlinear Parameter Estimation: An Integrated System in Basic
by John C. Nash
Publisher: Marcel Dekker Inc 1995
Number of pages: 493
This book and software collection is intended to help scientists, engineers and statisticians in their work. We have collected various software tools for nonlinear parameter estimation, along with representative example problems, and provided sufficient "glue" in the form of procedures, documentation, and auxiliary program code to allow for relatively easy use of the software system for nonlinear parameter estimation.
This document is no more available for free.
by I. F. Wilde
A gentle introduction to the mathematics of Stochastic Analysis. From the table of contents: Introduction; Conditional expectation; Martingales; Stochastic integration - informally; Wiener process; Ito's formula; Bibliography.
by S. Watanabe - Tata Institute of Fundamental Research
The author's main purpose in these lectures was to study solutions of stochastic differential equations as Wiener functionals and apply to them some infinite dimensional functional analysis. This idea was due to P. Malliavin.
by Gordan Žitković - The University of Texas at Austin
Contents: Probability review; Mathematica in 15 minutes; Stochastic Processes; Simple random walk; Generating functions; Random walks - advanced methods; Branching processes; Markov Chains; The 'Stochastics' package; Classification of States; etc.
by S.P. Meyn, R.L. Tweedie - Springer
The book on the theory of general state space Markov chains, and its application to time series analysis, operations research and systems and control theory. An advanced graduate text and a monograph treating the stability of Markov chains.