In ecological population management, years of animal counts are fit to nonlinear, dynamic models (e.g. the Ricker model) because the values of the parameters are of interest. The yearly counts are subject to measurement error, which inevitably leads to biased estimates and adversely affects...

Providing appropriate forecasts of time series data into the future depends crucially on whether the time series under consideration is non-stationary (i.e. has a unit root) or stationary. In the context of a Stochastic Volatility Model (SVM), the presence of a unit root in financial data has...

Statistical models involving latent variables are widely used in many areas of applications, such as biomedical science and social science. When likelihood-based parametric inferential methods are used to make statistical inference, certain distributional assumptions on the latent variables are...