Bayesian Inference for Stochastic Processes - Lyle D. Broemeling
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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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Description
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
More Information
| Author | Lyle D. Broemeling |
|---|---|
| Publisher | CRC Press |
| Release year | 2020 |
| Cover type | Softcover |
| EAN | 9780367572433 |