We construct geometric shrinkage priors for Kählerian signal filters. Based on the characteristics of Kähler manifold, an algorithm for finding the superharmonic priors is introduced. The algorithm is efficient and robust to obtain the Komaki priors. Several ansätze for the priors are also suggested. In particular, the ansätze related to Kähler potential are geometrically intrinsic priors to th...

Researchers in psychology are paying increasing attention to temporal correlations in performance on cognitive tasks. Recently, T. Thornton and D. L. Gilden (2005) introduced a spectral method for analysing psychological time series; in particular, this method is tailored to distinguish transient serial correlations from the persistent correlations characterised by 1/f noise. Thornton and Gilde...

We study the autocorrelation structure and the spectral density function of aggregates from a discrete-time process. The underlying discrete-time process is assumed to be a stationary AutoRegressive Fractionally Integrated MovingAverage (ARFIMA) process, after suitable number of differencing if necessary. We derive closed-form expressions for the limiting autocorrelation function and the normal...

Financial support from ESRC grant number L116251013, Macroeconomic Modelling and Policy Analysis in a Changing Word is gratefully acknowledged. The usual disclaimer applies. Fractional integrated ARMA (ARFIMA) models are investigated in this article for different measures of the UK unemployment. The analysis is carried out using the Sowell (1992) procedure of estimating by maximum likelihood in...

In this paper, we discuss two distinct multivariate time series models that extend the univariate ARFIMA model. We describe algorithms for computing the covariances of each model, for computing the quadratic form and approximating the determinant for maximum likelihood estimation, and for simulating from each model. We compare the speed and accuracy of each algorithm to existing methods and mea...

The article proposes a novel two-stage network traffic anomaly detection method for the railway transportation critical infrastructure monitored using wireless sensor networks (WSN). The first step of the proposed solution is to find and eliminate any outlying observations in the analyzed parameters of the WSN traffic using a simple and fast one-dimensional quartile criterion. In the second ste...

! ! The daily return and the realized volatility are simultaneously modeled in the stochastic volatility model with leverage and long memory. In addition to the stochastic volatility model with leverage for the daily returns, ARFIMA process is jointly considered for the realized volatilities. Using a state space representation of the model, we estimate parameters by Markov chain Monte Carlo met...