Random effects
in
AD Model Builder

Do you find standard statistical packages too restrictive?

ADMB-RE provides great flexibility for use of random effects in nonlinear models

Examples
Generalized linear mixed models (GLMM)
Nonlinear mixed models (nlme type)
State space models (nonlinear Kalman filter)
Frailty models in survival analysis
Semiparametric regression
Nonlinear spatial statistics
Stochastic volatility models

Fields of application
Statistical modelling
Financial time series
Fisheries assessments
Pharmacokinetics
Ecology

More details
Example collection
User manual

Technical details

  • Model specification in C++ like language
  • Hyper-parameters (variance components etc.) estimated by maximum likelihood
  • Marginal likelihood evaluated by the Laplace approximation or importance sampling
  • ADMB-RE calculates exact derivatives using Automatic Differentiation
  • All the useful features of ordinary AD Model Builder are available

Why choose ADMB-RE?

  • Flexibility: In principle you can implement any random effect you can think of
  • Convenience: Computional details are transparent. Your only responsability is to formulate the loglikelihood
  • Computational efficiency: ADMB-RE is up to 50 times faster than winBUGS
  • Robustness: With exact derivatives you can fit highly nonlinear models
  • Convergence diagnostic: The gradient of the likelihood function provides a clear convergence diagnostic, while with MCMC judging convergence is difficult.
Freely downloadable demo version comming soon!!