The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
A semiparametric Bayesian model for randomised block designs
Abstract
A model is proposed for a Bayesian semiparametric analysis of randomised block experiments. The model is a hierarchical model in which a Dirichlet process is inserted at the middle stage for the distribution of the block effects. This model allows an arbitrary distribution of block effects, and it results in effective estimates of treatment contrasts, block effects and the distribution of block effects. An effective computational strategy is presented for describing the posterior distribution.
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Citations
Cites
Sampling-based approaches to calculating marginal densities
Gelfand, A. E., & Smith, A. F. M. (1990) · Journal of the American Statistical Association · doi:10.1080/01621459.1990.10476213 · Cited by 6,606
Bayes Estimates for the Linear Model
Lindley, D. V., & Smith, A. F. M. (1972) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1972.tb00885.x · Cited by 2,025
Cited by
A statistical approach for identifying differential distributions in single-cell RNA-seq experiments
Korthauer, K. D., Chu, L.-F., Newton, M. A., Li, Y., Thomson, J., Stewart, R., & Kendziorski, C. (2016) · Genome Biology · doi:10.1186/s13059-016-1077-y · Cited by 273
Bayesian Analysis of Agricultural Field Experiments
Besag, J., & Higdon, D. (1999) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/1467-9868.00201 · Cited by 183
Metadata
- Authors
- Bush, C.
- Venue
- Biometrika
- Publisher
- Oxford University Press (OUP)
- Published
- 1996-06-01
- Volume
- 83
- Issue
- 2
- Pages
- 275-285
- ISSN
- 0006-3444 (ISSN-L)
- 1464-3510
- OpenAlex
- W2163229341
- Cited by
- 305
- References
- 2
- FWCI
- 12.02
- Type
- journal article
- Language
- en
- Open access
- closed
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