UID:
almahu_9949519832902882
Format:
VII, 151 p. 17 illus., 13 illus. in color.
,
online resource.
Edition:
1st ed. 2023.
ISBN:
9783031312823
Series Statement:
Synthesis Lectures on Mathematics & Statistics,
Content:
This book provides the essential theoretical tools for stochastic modeling. The authors address the most used models in applications such as Markov chains with discrete-time parameters, hidden Markov chains, Poisson processes, and birth and death processes. This book also presents specific examples with simulation methods that apply the topics to different areas of knowledge. These examples include practical applications, such as modeling the COVID-19 pandemic and animal movement modeling. This book is concise and rigorous, presenting the material in an easily accessible manner that allows readers to learn how to address and solve problems of a stochastic nature. .
Note:
Discrete-Time Markov Chain -- Branching Processes and Hidden Markov Model -- Poisson Processes and its Extensions -- Continuous-Time Markov Modeling -- Applications and Biology and Ecology.
In:
Springer Nature eBook
Additional Edition:
Printed edition: ISBN 9783031312816
Additional Edition:
Printed edition: ISBN 9783031312830
Additional Edition:
Printed edition: ISBN 9783031312847
Language:
English
DOI:
10.1007/978-3-031-31282-3
URL:
https://doi.org/10.1007/978-3-031-31282-3
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