Abstract
A stochastic process is a probability model that describes the evolution of a system evolving randomly in time. If we observe the system at a set of discrete times, say at the end of every day or every hour, we get a discrete-time stochastic process. On the other hand, if we observe the system continuously at all times, we get a continuous-time stochastic process. We begin with examples of the discrete- and continuous-time stochastic processes.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2011 Springer Science+Business Media, LLC
About this chapter
Cite this chapter
Kulkarni, V.G. (2011). Introduction. In: Introduction to Modeling and Analysis of Stochastic Systems. Springer Texts in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-1772-0_1
Download citation
DOI: https://doi.org/10.1007/978-1-4419-1772-0_1
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4419-1771-3
Online ISBN: 978-1-4419-1772-0
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)