In this paper, we systematically study the consistency of sliced average variance estimation (SAVE). The findings reveal that when the response is continuous, the asymptotic behavior of SAVE is rather different from that of sliced inverse regression (SIR). SIR can achieve √ n consistency even when each slice contains only two data points. However, SAVE cannot be √ n consistent and it even turns...

A generalised minimum variance controller is developed for linear time-varying systems. The plants to be controlled are described using a controlled autoregressive moving average model and are exponentially stable. Both, the plant parameters and the noise variance are time-varying. The generalised minimum variance cost functional is the sum of a tracking error variance between a filtered plant ...

Edge-aware smoothing is an essential tool for computer vision, graphics and photography. In this paper, we develop a new efficient local weighted average filter edge-aware smoothing. The proposed can use guidance information which permits iterative filtering process. Since the weights of depend on variance, implementation requires linear filters only, leading to $\mathcal {O}(N_{pix})$ computat...

This article investigates a Cautious Minimum Variance (CMV) control approach for controlling industrial process variability when the model parameters are estimated from data and subject to uncertainty. CMV control has a number of advantages over traditional robust control methods. It incorporates probabilistic, as opposed to deterministic, measures of parameter uncertainty, which are more consi...

There exist several methods developed for the canonical change point problem of detecting multiple mean shifts, which search changes over sections data at scales. In such methods, estimation noise level is often required in order to distinguish genuine from random fluctuations due noise. When serial dependence present, using a single estimator may not be appropriate. Instead, it proposed adopt ...