Now showing items 1-3 of 3

  • NLNG: A R Package for State Space Models 

    Hartling, Joey
    State space models require the ability to perform filtering, smoothing and prediction during analysis. To perform these procedures fairly complex computational algorithms are required. There is a consequent need for ...
  • Parameter Estimation for Nonlinear State Space Models 

    Wong, Jessica (2012-04-24)
    This thesis explores the methodology of state, and in particular, parameter estimation for time series datasets. Various approaches are investigated that are suitable for nonlinear models and non-Gaussian observations ...
  • Parameter, State and Uncertainty Estimation for 3-dimensional Biological Ocean Models 

    Mattern, Jann Paul (2012-08-23)
    Realistic physical-biological ocean models pose challenges to statistical techniques due to their complexity, nonlinearity and high dimensionality. In this thesis, statistical data assimilation techniques for parameter and ...