Skip to main content
King Abdullah University of Science and Technology
Bayesian Computational Statistics and Modeling
BAYESCOMP
Bayesian Computational Statistics and Modeling
Main navigation
  • Home
  • People
    • Principal Investigators
    • Research Scientists
    • Postdoctoral Fellows
    • Students
    • All Profiles
    • Alumni
    • Former Members
  • Events
    • All Events
    • Events Calendar
  • News
  • About
  • Research
  • Software
  • Contact Us

stochastic smoothing pipeline

Joint longitudinal-survival models using R-INLA

Janet van Niekerk, Research Scientist, Statistics
May 9, 12:00 - 13:00

B9 L2 H1

stochastic smoothing pipeline R-INLA

Joint models have received increasing attention during recent years with extensions into various directions; numerous hazard functions, different association structures, linear and non-linear longitudinal trajectories amongst others. They gained popularity amongst practitioners by the ability to incorporate various data sources. In this talk, we will introduce joint models and provide some conceptual ideas about their use and necessity. Also, we will illustrate how these models can be formulated as Latent Gaussian Models and hence be implemented using R-INLA.

Bayesian Computational Statistics and Modeling (BAYESCOMP)

Footer

  • A-Z Directory
    • All Content
    • Browse Related Sites
  • Site Management
    • Log in

© 2024 King Abdullah University of Science and Technology. All rights reserved. Privacy Notice