Corpus ID: 14550778

Bayesian nonparametric estimation of the spectral density of a long memory Gaussian time series

@article{Rousseau2006BayesianNE,
  title={Bayesian nonparametric estimation of the spectral density of a long memory Gaussian time series},
  author={J. Rousseau and B. Liseo},
  journal={arXiv: Statistics Theory},
  year={2006}
}
  • J. Rousseau, B. Liseo
  • Published 2006
  • Mathematics
  • arXiv: Statistics Theory
  • Let X = {Xt, t = 1, 2, . . . } be a stationary Gaussian random process, with mean EXt = and covariance function γ(τ ) = E(Xt − )(Xt+τ − ). Let f(λ) be the corresponding spectral density; a stationary Gaussian process is said to be long-range dependent, if the spectral density f(λ) can be written as the product of a slowly varying function ˜ f(λ) and the quantity λ−2d. In this paper we propose a novel Bayesian nonparametric approach to the estimation of the spectral density of X. We prove… CONTINUE READING
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