Advanced Bayesian Econometrics Python by Thatch Oliver (4 results)
- Softcover
Seller: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
Contact seller5-star sellerCondition: New
US$ 45.61
Free ShippingShips within U.S.A.Quantity: Over 20 available
PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
- Softcover
Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK
Contact seller5-star sellerCondition: New
US$ 43.18
US$ 5.53 shippingShips from United Kingdom to U.S.A.Quantity: Over 20 available
PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
- Softcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
Contact seller5-star sellerCondition: New
US$ 59.72
US$ 70.91 shippingShips from Germany to U.S.A.Quantity: 2 available
Taschenbuch. Condition: Neu. Neuware - Reactive PublishingThis book provides a comprehensive and practical treatment of advanced Bayesian econometrics using Python. It bridges modern machine learning techniques with traditional econometric modeling, offering detailed guidance on implementing state-of-the-art Bayesian methods for… complex economic problems.Readers will learn how to integrate deep learning priors, perform variational inference, work with Gaussian processes, and implement scalable MCMC algorithms tailored for high-dimensional economic models. The text emphasizes computational efficiency and practical application, addressing the challenges of estimation, uncertainty quantification, and model comparison in large-scale economic data.Key topics include: - Bayesian inference with neural network priors- Variational methods for fast posterior approximation- Gaussian process regression in econometric contexts- Scalable MCMC techniques for high-dimensional parameter spaces- Model selection, prediction, and policy analysis under uncertainty- End-to-end Python implementations using contemporary librariesWritten for graduate students, researchers, and practitioners in economics, finance, and data science, this book assumes familiarity with intermediate statistics, Python programming, and basic Bayesian concepts. All methods are demonstrated with reproducible code examples that translate directly to real-world economic modeling tasks.Clear explanations, mathematical derivations where needed, and practical coding guidance make this an essential resource for those seeking to move beyond standard econometric toolkits into more flexible and powerful Bayesian frameworks.
- Softcover
- Print on Demand
Seller: California Books, Miami, FL, U.S.A.California Books
Contact seller4-star sellerCondition: New
US$ 42.00
Free ShippingShips within U.S.A.Quantity: Over 20 available
Condition: New. Print on Demand.
