Keywords
Affiliated Institutions
Related Publications
Markov Chains
Markov chains are central to the understanding of random processes. This is not only because they pervade the applications of random processes, but also because one can calculat...
Stochastic Petri net representation of discrete event simulations
In the context of discrete event simulation, the marking of a stochastic Petri net (SPN) corresponds to the state of the underlying stochastic process of the simulation and the ...
CODA: convergence diagnosis and output analysis for MCMC
[1st paragraph] At first sight, Bayesian inference with Markov Chain Monte Carlo (MCMC) appears to be straightforward. The user defines a full probability model, perhaps using o...
Smooth Skyride through a Rough Skyline: Bayesian Coalescent-Based Inference of Population Dynamics
Kingman's coalescent process opens the door for estimation of population genetics model parameters from molecular sequences. One paramount parameter of interest is the effective...
Latent Class Model Diagnosis
Summary. In many areas of medical research, such as psychiatry and gerontology, latent class variables are used to classify individuals into disease categories, often with the i...
Publication Info
- Year
- 1999
- Type
- book
- Citations
- 752
- Access
- Closed
External Links
Social Impact
Social media, news, blog, policy document mentions
Citation Metrics
Cite This
Identifiers
- DOI
- 10.1007/978-1-4757-3124-8