A higher-order approximation to the marginal posterior distribution for a scalar parameter of interest in the presence of nuisance parameters is proposed. The approximation is obtained using a matching prior. The procedure improves the normal first-order approximation and has several advantages....

We discuss computational aspects of likelihood-based estimation of univariate ARFIMA (p,d,q) models. We show how efficient computation and simulation is feasible, even for large samples. We also discuss the implementation of analytical bias corrections.

We discuss computational aspects of likelihood-based estimation of unvariate ARFIMA (p,d,q) models. We show how efficient computation and simulation is feasible, even for large samples. We also discuss the implementation of analytical bias corrections.

We discuss computational aspects of likelihood-based specification, estimation,inference, and forecasting of possibly nonstationary series with long memory. We use the \ARFIMA$(p,d,q)$ model with deterministic regressors and we compare sampling characteristics of approximate and exact...