Nonparametric Bayesian Inference in Biostatistics
As chapters in this book demonstrate, BNP has important uses in clinical sciences and inference for issues like unknown partitions in genomics. Nonparametric Bayesian approaches (BNP) play an ever expanding role in biostatistical inference from use in proteomics to clinical trials. Many research pro...
| Συγγραφή απο Οργανισμό/Αρχή: | |
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| Άλλοι συγγραφείς: | , |
| Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
| Γλώσσα: | English |
| Έκδοση: |
Cham :
Springer International Publishing : Imprint: Springer,
2015.
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| Έκδοση: | 1st ed. 2015. |
| Σειρά: | Frontiers in Probability and the Statistical Sciences
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| Θέματα: | |
| Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- Part I Introduction
- Bayesian Nonparametric Models
- Bayesian Nonparametric Biostatistics
- Part II Genomics and Proteomics
- Bayesian Shape Clustering
- Estimating Latent Cell Subpopulations with Bayesian Feature Allocation Models
- Species Sampling Priors for Modeling Dependence: An Application to the Detection of Chromosomal Aberrations
- Modeling the Association Between Clusters of SNPs and Disease Responses
- Bayesian Inference on Population Structure: from Parametric to Nonparametric Modeling
- Bayesian Approaches for Large Biological Networks
- Nonparametric Variable Selection, Clustering and Prediction for Large Biological Datasets
- Part III Survival Analysis
- Markov Processes in Survival Analysis
- Bayesian Spatial Survival Models
- Fully Nonparametric Regression Modelling of Misclassified Censored Time-to-Event Data
- Part IV Random Functions and Response Surfaces
- Neuronal Spike Train Analysis Using Gaussian Process Models
- Bayesian Analysis of Curves Shape Variation through Registration and Regression
- Biomarker-Driven Adaptive Design
- Bayesian Nonparametric Approaches for ROC Curve Inference
- Part V Spatial Data
- Spatial Bayesian Nonparametric Methods
- Spatial Species Sampling and Product Partition Models
- Spatial Boundary Detection for Areal Counts
- A Bayesian Nonparametric Causal Model for Regression Discontinuity Designs
- Bayesian Nonparametrics for Missing Data in Longitudinal Clinical Trials.
