Buch, Englisch, 688 Seiten, Format (B × H): 165 mm x 241 mm, Gewicht: 1121 g
Buch, Englisch, 688 Seiten, Format (B × H): 165 mm x 241 mm, Gewicht: 1121 g
ISBN: 978-0-19-921465-5
Verlag: Oxford University Press
The Valencia International Meetings on Bayesian Statistics, held every four years, provide the main forum for researchers in the area of Bayesian Statistics to come together to present and discuss frontier developments in the field. Covering a broad range of applications and models, including genetics, computer vision and computation, the resulting proceedings provide a definitive, up-to-date overview encompassing a wide range of theoretical and applied research. This eighth proceedings includes edited and refereed versions of 20 invited papers plus extensive and in-depth discussion along with 19 extended four page abstracts of the best presentations offering a wide perspective of the developments in Bayesian statistics over the last four years.
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung
- Mathematik | Informatik EDV | Informatik Angewandte Informatik Computeranwendungen in Wissenschaft & Technologie
- Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Datenanalyse, Datenverarbeitung
- Technische Wissenschaften Technik Allgemein Computeranwendungen in der Technik
- Mathematik | Informatik EDV | Informatik Professionelle Anwendung Computer-Aided Design (CAD)
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
- Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
Weitere Infos & Material
- Generative or Discriminative? Getting the Best of Both Worlds
- Assessing the Effect of Genetic Mutation - A Bayesian Framework for Determining Population History from DNA Sequence Data
- Some Aspects of Bayesian Model Selection for Prediction
- Nonparametric Function Estimation Using Overcomplete Dictionaries
- Sequential Monte Carlo for Bayesian Computation
- Dynamic Gaussian Process Priors, with Applications to The Analysis of Space-time Data
- Bayesian Nonparametric Modelling for Spatial Data Using Dirichlet Processes
- Bayesian Nonparametric Latent Feature Models
- Objective Bayesian Analysis of Multiple Changepoints for Linear Models
- Bayesian Relaxation: Boosting, The Lasso, and other L norms
- The Bayesian Approach to the Analysis of Finite Population Surveys
- Detecting selection in DNA sequences: Bayesian Modelling and Inference
- Deriving Bayesian and frequentist estimators from time-invariance estimating equations: a unifying approach
- FDR and Bayesian Multiple Comparisons Rules
- Estimating the Integrated Likelihood via Posterior Simulation Using the Harmonic Mean Identity.
- Approximating Interval Hypothesis: p-values and Bayes Factors
- Bayesian Probability in Quantum Mechanics
- Fast Bayesian Shape Matching Using Geometric Algorithms
- Nested Sampling for Bayesian Computations
- Objective Bayesian Analysis for the Multivariate Normal Model
- CONTRIBUTED PAPERS
- Almeida, C. and Mouchart, M.: Bayesian Encompassing Specification Test Under Not Completely Known Partial Observability
- Bernardo, J. M. and P´erez, S.: Comparing Normal Means: New Methods for an Old Problem
- Cano, J. A., Kessler, M. and Salmer´on, D.: Integral Priors for the One Way Random Effects Model
- Carvalho, C. M. and West, M.: Dynamic Matrix-Variate Graphical Models
- Cowell, R. G., Lauritzen, S.L. and Mortera, J.: A Gamma Model for DNA Mixture Analyses
- Denham, R. J. and Mengersen, K.: Geographically Assisted Elicitation of Expert Opinion for Regression Models
- Duki´c, V. and Dignam, J.: Hierarchical Multiresolution Hazard Model for Breast Cancer Recurrence
- Hutter, M.: Bayesian Regression of Piecewise Constant Functions
- Jirsa, J., Quinn, A. and Varga, F.: Identification of Thyroid Gland Activity in Radiotherapy.
- Kokolakis, G. and Kouvaras, G.: Partial Convexification of Random Probability Measures
- Ma, H. and Carlin, B. P.: Bayesian Multivariate Areal Wombling
- Madrigal, A. M.: Cluster Allocation Design Networks
- Mertens, B. J. A.: Logistic Regression Modelling of Proteomic Mass Spectra in a Case-Control Study on Diagnosis for Colon Cancer
- Møller, J. and Mengersen, K.: Ergodic Averages Via Dominating Processes
- Perugia, M.: Bayesian Model Diagnostics Based on Artificial Autoregressive Errors
- Short, M. B., Higdon, D. M. and Kronberg, P. P.: Estimation of Faraday Rotation Measures of the Near Galactic Sky, Using Gaussian Process Models
- Spitzner, D. J.: An Asymptotic Viewpoint on High-Dimensional Bayesian Testing
- Wallstrom, T. C.: The Marginalization Paradox and Probability Limits Xing, E. P. and Sohn, K.-A.: A Hidden Markov Dirichlet Process Model for Genetic Recombination in Open Ancestral Space
