In this paper, we present a review of Shannon and differential entropy rate estimation
techniques. Entropy rate, which measures the average information gain from a stochastic …

Focusing on Bayesian approaches and computations using simulation-based methods for
inference, Time Series: Modeling, Computation, and Inference integrates mainstream …

This paper reviews alternative methods for estimation for stationary Gegenbauer processes
specifically, as distinct from the more general long memory models. A short set of Monte …

This article describes a Bayesian approach to estimating the spectral density of a stationary
time series. A nonparametric prior on the spectral density is described through Bernstein …

We present a new Bayesian nonparametric approach to estimating the spectral density of a
stationary time series. A nonparametric prior based on a mixture of B-spline distributions is …

This paper draws its motivation from applications in geophysics, agricultural, and
environmental sciences where empirical evidence of slow decay of correlations have been …

Supplementary material to 'Beyond Whittle: Nonparametric Correction of a Parametric
Likelihood with a Focus on Bayesian Time Series Analysis'. The electronic supplement …

We develop a novel Bayesian modeling approach to spectral density estimation for multiple
time series. The log-periodogram distribution for each series is modeled as a mixture of …

Many geophysical quantities, such as atmospheric temperature, water levels in rivers, and
wind speeds, have shown evidence of long memory (LM). LM implies that these quantities …

Bayesian nonparametric estimation of the spectral density of a long or intermediate memory
Gaussian process Page 1 The Annals of Statistics 2012, Vol. 40, No. 2, 964–995 DOI …