Bayesian Inference for Stochastic Processes
Book Details
Format
Paperback / softback
ISBN-10
0367572435
ISBN-13
9780367572433
Publisher
Taylor & Francis Ltd
Imprint
Chapman & Hall/CRC
Country of Manufacture
GB
Country of Publication
GB
Publication Date
Jun 30th, 2020
Print length
432 Pages
Weight
830 grams
Product Classification:
Mathematics & scienceMathematics and ScienceProbability & statisticsProbability and statistics
KSh 10,150.00
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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
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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