Testing the fractionally integrated order of seasonal and non-seasonal unit roots is quite important for the economic and financial time series modelling. In this paper, Robinson test (1994) is applied to various well-known long memory models. Via Monte Carlo experiments, we study and compare...

Testing the fractionally integrated order of seasonal and non-seasonal unit roots is quite important for the economic and financial time series modelling. In this paper, Robinson test (1994) is applied to various well-known long memory models. Via Monte Carlo experiments, we study and compare...

The aim of this work is to provide the reader with a brief overview of the foundations of human memory from the perspective of Cognitive Psychology, in order to supply a theoretical framework to assess the scientific plausibility and validity of terms such as 'collective memory', 'social memory'...

Gaussian time-series models are often specified through their spectral density. Such models pose several computational challenges, in particular because of the non-sparse nature of the covariance matrix. We derive a fast approximation of the likelihood for such models. We use importance sampling...

A general moment bound for sums of products of Gaussian vector’s functions extending the moment bound in Taqqu (1977, Lemma 4.5) [28] is established. A general central limit theorem for triangular arrays of nonlinear functionals of multidimensional non-stationary Gaussian sequences is proved....

We consider the estimation of the location of the pole and memory parameter, λ0 and α respectively, of covariance stationary linear processes whose spectral density function f(λ) satisfies f(λ) ∼ C|λ − λ0|−α in a neighbourhood of λ0. We define a consistent estimator of λ0 and...

A stationary Gaussian process is said to be long-range dependent (resp., anti-persistent) if its spectral density f(λ) can be written as f(λ)=|λ|−2dg(|λ|), where 0d1/2 (resp., −1/2d0), and g is continuous and positive. We propose a novel Bayesian nonparametric approach for the estimation...