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

Real-time signal extraction is about the definition and the estimation of signals at the current
boundary of time series. Accessory, this book is also about the early detection of turning …

This paper expounds some of the results of Fourier theory that are essential to the statistical
analysis of time series. It employs the algebra of circulant matrices to expose the structure of …

Reasonable prediction makes significant practical sense to stochastic and unstable time
series analysis with small or limited sample size. Motivated by the rolling idea in grey theory …

The toxicity and efficacy of more than 30 anticancer agents present very high variations,
depending on the dosing time. Therefore, the biologists studying the circadian rhythm …

Forecasting of fluctuations in worldwide food prices is of considerable practical importance–
however, it is also difficult, especially for longer horizons. Standard econometric models …

In this thesis, we consider two classes of long memory processes: the stationary long
memory processes and the non-stationary long memory processes. We are devoted to the …

We propose a Bayesian procedure for exploiting small, possibly long-lag linear predictability
in the innovations of a finite order autoregression. We model the innovations as having a log …

We consider the problem of unobserved components in time series from a Bayesian non-
parametric perspective. The identification conditions are treated as unknown and analyzed …

Estimation of seasonal demand prior to an active demand season is essential in supply
chain management. The business cycle of the seasonal demand is divided into two stages …