Projects per year
Abstract
The R package contains different MCMC schemes to estimate the regression coefficients of a binomial (or binary) logit model within a Bayesian framework: a data-augmented independence MH-sampler, an auxiliary mixture sampler and a hybrid auxiliary mixture (HAM) sampler. All sampling procedures are based on algorithms using data augmentation, where the regression coefficients are estimated by rewriting the logit model as a latent variable model called difference random utility model (dRUM).
| Original language | English |
|---|---|
| Publication status | Published - 2012 |
Fields of science
- 102009 Computer simulation
- 101018 Statistics
- 101 Mathematics
- 103 Physics, Astronomy
- 105 Geosciences
- 305 Other Human Medicine, Health Sciences
- 504 Sociology
- 106 Biology
- 502 Economics
- 509 Other Social Sciences
JKU Focus areas
- Social Systems, Markets and Welfare States
- Social and Economic Sciences (in general)
Projects
- 2 Active
-
Bayesian statistics and MCMC methods
Hainy, M. (Researcher) & Wagner, H. (PI)
01.01.2012 → 31.12.2025
Project: Other › Project from scientific scope of research unit
-
Categorical data analysis
Duller, C. (Researcher) & Wagner, H. (PI)
01.01.2012 → 31.12.2025
Project: Other › Project from scientific scope of research unit