A Bayesian approach to the analysis of quantal bioassay studies using nonparametric mixture models
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Publication:4979231
DOI10.1111/biom.12120zbMath1419.62351OpenAlexW1561318342WikidataQ45182899 ScholiaQ45182899MaRDI QIDQ4979231
Athanasios Kottas, Kassandra Fronczyk
Publication date: 17 June 2014
Published in: Biometrics (Search for Journal in Brave)
Full work available at URL: https://escholarship.org/uc/item/0x35c992
Markov chain Monte Carlocalibrationdependent Dirichlet processdose-response curvenonparametric mixture modelscytogenetic dosimetry
Nonparametric regression and quantile regression (62G08) Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15)
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- A Dirichlet process mixture model for the analysis of correlated binary responses
- Bayesian bioassay design
- Posterior distribution of a Dirichlet process from quantal response data
- Mixtures of Dirichlet processes with applications to Bayesian nonparametric problems
- A Bayesian nonparametric approach to determining a maximum tolerated dose
- A Bayesian analysis of some nonparametric problems
- On the support of MacEachern's dependent Dirichlet processes and extensions
- A Nonparametric Bayesian Modeling Approach for Cytogenetic Dosimetry
- Bayesian Nonparametric Nonproportional Hazards Survival Modeling
- Probits of Mixtures
- Bayesian Nonparametric Estimation of Continuous Monotone Functions with Applications to Dose–Response Analysis
- Linear Bayes estimators of the potency curve in bioassay
- Nonparametric Bayesian bioassay including ordered polytomous response
- Markov chain Monte Carlo in approximate Dirichlet and beta two-parameter process hierarchical models
- Bayesian Nonparametric Inference on the Dose Level with Specified Response Rate
- Bayesian Nonparametric Inference for Effective Doses in a Quantal-Response Experiment
- Gibbs Sampling Methods for Stick-Breaking Priors
- A Bayesian Nonparametric Modeling Framework for Developmental Toxicity Studies
- A Bayesian Semiparametric Approach for Solving the Discrete Calibration Problem
- An ANOVA Model for Dependent Random Measures
