'Mcmc algorithm' presentation slideshows

Random effect modelling of great tit nesting behaviour

Random effect modelling of great tit nesting behaviour. William Browne (University of Nottingham) In collaboration with Richard Pettifor (Institute of Zoology, London), Robin McCleery and Ben Sheldon (University of Oxford). Talk Summary. Background. Wytham woods great tit dataset.

587 views • 42 slides

Animation CS 551 / 651

Animation CS 551 / 651. Chenney & Forsyth, 2000. Chenney/Forsyth Paper. Results. Applications Atoms: 200 spheres and 100 water molecules in divided box Cars: 4 multibody vehicles and 400 pendula Robots: 20 eight-link manipulators throwing blocks

508 views • 36 slides

Bayesian Integration (MCMC II)

Bayesian Integration (MCMC II). Lecture 10. Why Diagnostic Statistics?. There is no guarantee, no matter how long you run the MCMC algorithm for, that it will converge to the posterior distribution.

704 views • 35 slides

Evaluating and quantifying benefit of exposure-response modeling for dose finding

513 views • 35 slides

Graphical Diagnostic Tools for Evaluating Latent Class Models: An Application to Depression in the ECA Study

Graphical Diagnostic Tools for Evaluating Latent Class Models: An Application to Depression in the ECA Study. Elizabeth S. Garrett. Department of Biostatistics Johns Hopkins University. GOAL. Provide tools for choosing the most appropriate latent class model.

618 views • 27 slides

Introduction to Statistical Models for longitudinal network data

Introduction to Statistical Models for longitudinal network data. Stochastic actor-based models Kayo Fujimoto, Ph.D. Stochastic actor-based model (Snijders 2001, 2005). Actor-oriented modeling Methodological individualism Modeled as a consequence of actors: Making new choices

204 views • 18 slides