-
-
Notifications
You must be signed in to change notification settings - Fork 481
BUGS Examples Sorted Alphabetically
Peter Li edited this page Aug 11, 2014
·
2 revisions
- Air: "Berkson measurement error"
- Alligators: "multinomial logistic model"
- Asia: "expert system"
- BUGS Background
- [Stan Files] n/a, requires marginalizing 5 binary categorical values; see issue 517 if you'd like to do it
- [Stan Code] n/a
- Beetles: "choice of link function"
- Biopsies: "discrete variable latent class model"
- Birats: "a bivariate normal hierarchical model"
- Blocker: "random effects meta-analysis of clinical trials"
- Bones: "latent trait model for multiple ordered categorical responses"
- Camel: "multivariate normal with structured missing data"
- Cervix: "case - control study with errors in covariates"
- Data Cloning: "Using Data Cloning to Calculate MLEs for the Seeds Model"
- Dogs: "loglinear model for binary data"
- Dugongs: "nonlinear growth curve"
- Dyes: "variance components model"
- Endo: "conditional inference in case-control studies"
- Epilepsy: "repeated measures on Poisson counts"
- Equiv: "bioequivalence in a cross-over trial"
- Eyes: "Normal Mixture Model"
- Fire Insurance Claims: "data distribution using dloglik"
- Fun Shapes: "general constraints"
- Hearts: "a mixture model for count data"
- Hepatitis: "random effects model with measurement error"
- Ice: "non-parametric smoothing in an age-cohort model"
- Inhalers: "ordered catagorical data"
- Jaws: "repeated measures analysis of variance"
- Kidney: "Weibull regression with random efects"
- Litter
- Leuk: "Cox regression"
- LeukFr: "Cox regression with random effects"
- LSAT: "item response"
- Magnesium: "Sensitivity to prior distributions"
- Mice: "Weibull regression"
- Multivariate Normal Orange Trees: "Non-linear growth curve"
- Orange Trees: "Non-linear growth curve"
- Oxford: "smooth fit to log-odds ratios"
- Pumps: "conjugate gamma-Poisson hierarchical model"
- Rats: "a normal hierarchical model"
- Salm: "extra - Poisson variation in dose - response study "
- Schools: "ranking school examination results using multivariate hierarchical models"
- Seeds: "Random effect logistic regression"
- Stacks: "robust regression"
- Stagnant: "a changepoint problem and an illustration of how NOT to do MCMC!"
- Simulating Data: "learning about the degrees of freedom of a t-distribution "
- Surgical: "Institutional ranking"