Statistical Modeling Using Bayesian Latent Gaussian Models With Applications in Geophysics and Environmental Sciences /
This book focuses on the statistical modeling of geophysical and environmental data using Bayesian latent Gaussian models. The structure of these models is described in a thorough introductory chapter, which explains how to construct prior densities for the model parameters, how to infer the paramet...
Gorde:
| Erakunde egilea: | |
|---|---|
| Beste egile batzuk: | |
| Formatua: | Baliabide elektronikoa eBook |
| Hizkuntza: | ingelesa |
| Argitaratua: |
Cham :
Springer International Publishing : Imprint: Springer,
2023.
|
| Edizioa: | 1st ed. 2023. |
| Gaiak: | |
| Sarrera elektronikoa: | https://doi.org/10.1007/978-3-031-39791-2 |
| Etiketak: |
Etiketa erantsi
Etiketarik gabe, Izan zaitez lehena erregistro honi etiketa jartzen!
|
Aurkibidea:
- Preface
- Chapter 1. Birgir Hrafnkelsson and Haakon Bakka: Bayesian latent Gaussian models
- Chapter 2. Giri Gopalan, Andrew Zammit-Mangion, and Felicity McCormack: A review of Bayesian modelling in glaciology
- Chapter 3. Birgir Hrafnkelsson, Rafael Daniel Vias, Solvi Rognvaldsson, Axel Orn Jansson, and Sigurdur M. Gardarsson: Bayesian discharge rating curves based on the generalized power law
- Chapter 4. Sahar Rahpeyma, Milad Kowsari, Tim Sonnemann, Benedikt Halldorsson, and Birgir Hrafnkelsson: Bayesian modeling in engineering seismology: Ground-motion models
- Chapter 5. Atefe Darzi, Birgir Hrafnkelsson, and Benedikt Halldorsson: Bayesian modelling in engineering seismology: Spatial earthquake magnitude model
- Chapter 6. Joshua Lovegrove and Stefan Siegert: Improving numerical weather forecasts by Bayesian hierarchical modelling
- Chapter 7. Arnab Hazra, Raphael Huser, and Arni V. Johannesson: Bayesian latent Gaussian models for high-dimensional spatial extremes.