Stochastic Processes and Their Applications
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A01=Frank Beichelt
A01=L. Paul Fatti
advanced stochastic process applications
Alternating Renewal Process
applied probability theory
Author_Frank Beichelt
Author_L. Paul Fatti
Autoregressive Sequence
Category=KCH
Category=PBT
Category=PBW
Continuous Time Markov Chain
Covariance Function
Delayed Renewal Process
Discrete Time Markov Chains
Distribution Function
eq_bestseller
eq_business-finance-law
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Forward Recurrence Time
Homogeneous Poisson Process
Inhomogeneous Poisson Process
Markov Chain
Minimal Repair
Ordinary Renewal Process
probability models
Queueing System
random processes
Random Telegraph Signal
Renewal Counting Process
Renewal Function
Sample Path
semi-Markov Process
Stationary State Distribution
Stationary State Probabilities
statistical inference
stochastic modelling
time series analysis
Transition Matrix
Wide Sense Stationary
Wide Sense Stationary Process
Wiener Process
Product details
- ISBN 9780415272322
- Weight: 790g
- Dimensions: 178 x 254mm
- Publication Date: 18 Oct 2001
- Publisher: Taylor & Francis Ltd
- Publication City/Country: GB
- Product Form: Hardback
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This book introduces stochastic processes and their applications for students in engineering, industrial statistics, science, operations research, business, and finance. It provides the theoretical foundations for modeling time-dependent random phenomena encountered in these disciplines. Through numerous science and engineering-based examples and exercises, the author presents the subject in a comprehensible, practically oriented way, but he also includes some important proofs and theoretically challenging examples and exercises that will appeal to more mathematically minded readers. Solutions to most of the exercises are included either in an appendix or within the text.
