- Tuyl, Frank, Gerlach, Richard, Mengersen, Kerrie
A comparison of bayes-laplace, jeffreys, and other priors: the case of zero events
- Tuyl, Frank, Gerlach, Richard, Mengersen, Kerrie
A method to handle zero counts in the multinomial model
A note on priors for the multinomial model
An empirical examination of the pricing of exchange-traded barrier options
- Easton, Stephen Andrew, Gerlach, Richard Helmut, Graham, Melissa, Tuyl, Frank
Bayesian Benefits for Binomial Applications in Practice
Conditional probability and HIV testing: a real-world example (letter)
Consensus priors for multinomial and binomial ratios
- Tuyl, Frank, Gerlach, Richard, Mengersen, Kerrie
Consensus priors in the presence of general laws
- Tuyl, Frank, Gerlach, Richard, Mengersen, Kerrie
Diagnostic testing: a simple approximate interval for the positive predictive value
Equidistribution testing with Bayes factors and the ECT
- Stokes, Barrie, Tuyl, Frank, Hudson, Irene
Flutracking: a weekly Australian community online survey of influenza-like illness in 2006, 2007 and 2008
- Dalton, Craig, Durrheim, David, Fejsa, John, Francis, Lynn, Carlson, Sandra, Tursan d'Espaignet, Edouard, Tuyl, Frank
- Bilano, Ver, Gilmour, Stuart, Moffiet, Trevor, d'Espaignet, Edouard Tursan, Stevens, Gretchen A., Commar, Alison, Tuyl, Frank, Hudson, Irene, Shibuya, Kenji
Household disaster preparedness and information sources: rapid cluster survey after a storm in New South Wales, Australia
- Cretikos, Michelle, Eastwood, Keith, Dalton, Craig, Merritt, Tony, Tuyl, Frank, Winn, Linda, Durrheim, David
Influenza: H1N1 goes to school
- Paterson, Bev, Durrheim, David N., Tuyl, Frank
MCMC methods for comparing stochastic volatility and GARCH models
- Gerlach, Richard, Tuyl, Frank
New prior sampling methods for nested sampling - development and testing
- Stokes, Barrie, Tuyl, Frank, Hudson, Irene
On the Certainty of an Inductive Inference: The Binomial Case
- Tuyl, Frank, Gerlach, Richard, Mengersen, Kerrie
- Tuyl, Frank, Gerlach, Richard, Mengersen, Kerrie
Simplifying life through Bayes: hints for practitioners new to Bayesian inference
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