Motivated by the method for color image segmentation based on intensity and hue clustering proposed in [26] we give some theoretical explanations for this method that directly follows from the natural connection between the maximum likelihood approach and Least Squares or Least Absolute Deviations clustering optimality criteria. The method is tested and illustrated on a few typical situations, ...

This paper presents a general robust solution for the problem of affine object matching, whereby an object can be given as a discrete point set, a set of lines, or a closed region. Let be given two such objects which are related by a general affine transformation (up to noise and maybe some additional distortions of the object). Then we can determine the six parameters aik of the affine transfo...

In this paper we describe and present results on the parameter point estimation for the scale and threshold parameters of the Rayleigh distribution. Five estimating methods have been investigated, namely, the maximum likelihood, the method of moment, the probability weighted moments method, the least square method and the least absolute deviation method. Modified maximum likelihood estimators f...

In this paper we describe active set type algorithms for minimization of a smooth function under general order constraints, an important case being functions on the set of bimonotone r × s matrices. These algorithms can be used, for instance, to estimate a bimonotone regression function via least squares or (a smooth approximation of) least absolute deviations. Another application is shrinkage ...

1 Mining public transportation networks is a growing and explosive challenge due to the increasing number of information available. In highly populated urban zones, the vehicles can often fail the schedule. Such fails cause headway deviations (HD) between high-frequency bus pairs. In this paper, we propose to identify systematic HD which usually provokes the phenomenon known as Bus Bunching (BB...

In this paper, an algorithm for sparse channel estimation, called ‘1-regularized leastabsolutes (‘1-LA), and an algorithm for equalization, called linear least-absolutes (LLA), in non-Gaussian impulsive noise are proposed. The proposed approaches are based on the minimization of the absolute error function, rather than the squared error function. By replacing the standard modulus with the ‘1-mo...

This article advances our understanding of regression-based data mining by comparing the utility of Least Absolute Value (LAV) and Least Squares (LS) regression methods. Using demographic variables from U.S. state-wide data, we fit variable regression models to dependent variables of varying distributions using both LS and LAV. Forecasts generated from the resulting equations are used to compar...

Standard control charts are constructed under the assumption that the observations taken from the process of interest are independent over time; however, in practice the observations in many cases are actually correlated. This paper considers the problem of monitoring a process in which the observations can be represented as a first-order autoregressive model following a heavy tailed distributi...

The use of correntropy as a similarity measure has been increasing in different scenarios due to the well-known ability to extract high-order statistic information from data. Recently, a new similarity measure between complex random variables was defined and called complex correntropy. Based on a Gaussian kernel, it extends the benefits of correntropy to complex-valued data. However, its proper...