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Bayesian Inference for Stochastic Processes

About Bayesian Inference for Stochastic Processes

The book aims to introduce Bayesian inference methods for stochastic processes. The Bayesian approach has advantages compared to non-Bayesian, among which is the optimal use of prior information via data from previous similar experiments. Examples from biology, economics, and astronomy reinforce the basic concepts of the subject. R a

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  • Language:
  • English
  • ISBN:
  • 9780367572433
  • Binding:
  • Paperback
  • Pages:
  • 432
  • Published:
  • June 29, 2020
  • Dimensions:
  • 178x254x0 mm.
  • Weight:
  • 453 g.
Delivery: 1-2 weeks
Expected delivery: November 30, 2024

Description of Bayesian Inference for Stochastic Processes

The book aims to introduce Bayesian inference methods for stochastic processes. The Bayesian approach has advantages compared to non-Bayesian, among which is the optimal use of prior information via data from previous similar experiments. Examples from biology, economics, and astronomy reinforce the basic concepts of the subject. R a

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