We propose a new iterative distributed estimation algorithm for Gaussian hidden Markov graphical models with loops. We decompose a loopy graph into a number of linked ernbedded triangles and then apply a parallel block-lacohi iteration comprising local linear minimum mean-square-error estimation on each triangle (involving a simple 3 x 3 matrix inverse computation) followed by an information ex...

The local model network is a set of models, each describing the same dynamic system but at different operating points. The outputs of these local models are weighted according to the current operating point and summed to give the local model network output. A local model network can be constructed from nonlinear continuous local models. The parameters of the local models can be identified using...

This study considers variance estimation when estimating the asymptotic variance of a propensity score matching estimator for the average treatment effect. We investigate the role of smoothing parameters in a variance estimator based on matching. We also study the properties of estimators using local linear estimation. Simulations demonstrate that large gains can be made in terms of mean square...

Abstract. In this paper, we study the estimation of a function based on noisy inhomogeneous data (the amount of data can vary on the estimation domain). We consider the model of regression with random design, where the design density is unknown. We construct an asymptotically sharp estimator which converges, for sup norm error loss, with a spatially dependent normalisation which is sensitive to...

High-frequency (HF) radars are routinely used for remotely sensing ocean surface currents. However, the performance of the most widely used direction-finding HF radar is degraded due to the effect of the inevitable deviations of actual antenna pattern on the direction of arrival (DOA) estimation. In this paper, we quantify the DOA estimation error resulting from the deviation of the actual ante...

Recently, quantile regression (QR) models are often applied for longitudinal data analysis. When the distribution of responses seems to be skew and asymmetric due to outliers and heavy-tails, QR models may work suitably. In this paper, a semi-parametric quantile regression model is developed for analysing continuous longitudinal responses. The error term's distribution is assumed to be Asymmetr...

"Population estimates have important implications for resource allocation within government and commerce, and are often assumed to be without error. Currently, central government provides annual population estimates for all the local and health authority districts in Britain, but estimates are needed for smaller areas, typically for electoral wards and postal sectors. Small area estimates are p...

We consider parameter estimation for time-dependent locally stationary long-memory processes. The asymptotic distribution of an estimator based on the local infinite autoregressive representation is derived, and asymptotic formulas for the mean squared error of the estimator, and the asymptotically optimal bandwidth are obtained. In spite of long memory, the optimal bandwidth turns out to be of...

In orthogonal frequency-division multiplexing (OFDM)based wireless local area networks (WLANs), phase noise (PHN) and residual frequency offset (RFO) can cause the common phase error (CPE) and the inter-carrier interferences (ICI), which seriously degrade the performance of systems. In this letter, we propose a combined pilot symbol assisted and decision-directed channel estimation scheme based...

One of the modern scientific methods researching phenomena and pro-cesses is mathematical modeling, which in many cases allows replacing real process makes it possible to obtain both a qualitative quantitative pic-ture process. Since exact solutions such models can be found very individual cases, necessary use approximate methods. In applied mathematics, fractional-rational approximations, unde...