FELLS: fast estimator of latent local structure

A Two-Phase Robust Estimation of Process Dispersion Using M-estimator

Parameter estimation is the first step in constructing any control chart. Most estimators of mean and dispersion are sensitive to the presence of outliers. The data may be contaminated by outliers either locally or globally. The exciting robust estimators deal only with global contamination. In this paper a robust estimator for dispersion is proposed to reduce the effect of local contamination ...

Spectral Experts for Estimating Mixtures of Linear Regressions

Discriminative latent-variable models are typically learned using EM or gradient-based optimization, which suffer from local optima. In this paper, we develop a new computationally efficient and provably consistent estimator for a mixture of linear regressions, a simple instance of a discriminative latentvariable model. Our approach relies on a lowrank linear regression to recover a symmetric t...

A New Class of Decentralized Interaction Estimators for Load Frequency Control in Multi-Area Power Systems

Load Frequency Control (LFC) has received considerable attention during last decades. This paper proposes a new method for designing decentralized interaction estimators for interconnected large-scale systems and utilizes it to multi-area power systems. For each local area, a local estimator is designed to estimate the interactions of this area using only the local output measurements. In fact,...

The Structure of Bhattacharyya Matrix in Natural Exponential Family and Its Role in Approximating the Variance of a Statistics

In most situations the best estimator of a function of the parameter exists, but sometimes it has a complex form and we cannot compute its variance explicitly. Therefore, a lower bound for the variance of an estimator is one of the fundamentals in the estimation theory, because it gives us an idea about the accuracy of an estimator. It is well-known in statistical inference that the Cram&eac...

A. Fells