Buch, Englisch, 592 Seiten, Format (B × H): 167 mm x 231 mm, Gewicht: 1080 g
Buch, Englisch, 592 Seiten, Format (B × H): 167 mm x 231 mm, Gewicht: 1080 g
ISBN: 978-0-12-283955-9
Verlag: ACADEMIC PR INC
Markov process theory is basically an extension of ordinary calculus to accommodate functions whos time evolutions are not entirely deterministic. It is a subject that is becoming increasingly important for many fields of science. This book develops the single-variable theory of both continuous and jump Markov processes in a way that should appeal especially to physicists and chemists at the senior and graduate level.
Zielgruppe
Professionals/scientists without training in probability and statistics (using books as a "self-help" guide), senior undergraduate and graduate level students in physics and chemistry and mathematicians specializing in game theory, and finite math.
Autoren/Hrsg.
Fachgebiete
- Naturwissenschaften Biowissenschaften Angewandte Biologie Biomathematik
- Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
- Naturwissenschaften Chemie Chemie Allgemein Chemometrik, Chemoinformatik
- Technische Wissenschaften Technik Allgemein Mathematik für Ingenieure
- Technische Wissenschaften Bauingenieurwesen Mathematische Methoden, Computeranwendungen (Bauingenieurwesen)
- Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung
Weitere Infos & Material
Random Variable Theory General Features of a Markov Process Continuous Markov Processes Jump Markov Processes with Continuum States Jump Markov Processes with Discrete States Temporally Homogeneous Birth-Death Markov Processes Appendixes: Some Useful Integral Identities Integral Representations of the Delta Functions An Approximate Solution Procedure for "Open" Moment Evolution Equations Estimating the Width and Area of a Function Peak Can the Accuracy of the Continuous Process Simulation Formula Be Improved? Proof of the Birth-Death Stability Theorem Solution of the Matrix Differential Equation
