Search results for "Outlier"

Outlier detection to hierarchical and mixed effects models

2008

Hierarchical and mixed effects models are models where a varying number of coefficients may be random at different levels of the hierarchy. The purpose of outlier analysis for these models is to determine whether an outlying unit at higher level is entirely outlying, or outlying due to effect of one or a few aberrant lower level units. Most works on diagnostics for these complex models have focused on the mixed model rather than on the hierarchical models, obscuring some relevant aspects of the hierarchical model. In this paper we will present an approach to influence analysis and outlier detection for mixed and hierarchical model, focusing on the special structure of nested data that these…

Geometric quality and appearance of surfaces : local and global approaches

2012

Accounting for customers' perception of manufactured goods has become a major challenge for the industry. This process is to be established from early design to retail. Customers are nowadays more aware and detail oriented about perceived quality of products. This allows one to set not only an estimated price but also the expected quality of the product. Surface appearance analysis has therefore become a key industrial issue. Two approaches are proposed here to formalize the detection methodology and provide objective criteria for experts to evaluate surface anomalies. The first proposed approach is based on surface metrology. It consists in analyzing the measured topologies in order to bin…

Outlier recognition in crystal-structure least-squares modelling by diagnostic techniques based on leverage analysis.

2005

The identification of the actual outliers in a least-squares crystal-structure model refinement and their subsequent elimination from the data set is a non-trivial task that has to be carried out carefully when a high level of accuracy of the estimates is required. One of the most suitable tools for detecting the influence of each data entry on the regression is the identification of ;leverage points'. On the other hand, the recognition of the actual statistical outliers is effectively possible by using some diagnostics as a function of the leverage, such as Cook's distance, DFFITS and FVARATIO. The evaluation of these estimators makes it possible to achieve a reliable identification of the…

A multivariate approach to the study of orichalcum ingots from the underwater Gela's archaeological site

2017

Abstract In this work a careful ICP-OES and ICP-MS investigation of 38 ancient ingots has been performed to determine both major components and trace elements content to find a correlation between the observed different features and the composition. The ingots, recovered in an underwater archaeological site of various finds near Gela (CL, Italy), were previously investigated by X-Ray Fluorescence (XRF) spectroscopy to know the composition of the alloy and it was found that the major elements were copper and zinc, in a ratio compatible with the famous orichalcum similar to the contemporary brass that was considered a precious metal in ancient times. The discovery of huge amount this alloy is…

I: Boxplots - die flexible Alternative zum „Antennenbildchen”

2002

Data description for continuous parameters is sometimes only based on means and standard deviations of measurement series, graphical representation only concentrates on corresponding "MSE plots", which provide means and standard deviations or even only mean squared errors. However, this strategy is only correct for normally distributed data. Outliers may seriously bias mean and standard deviations and may therefore lead to wrong clinical conclusions. The present paper suggests the use of medians and quartiles, which - just like their graphical pendant, the nonparametric "box whisker plot" - can be applied much more flexibly.

An informal procedure to detect outliers in multilevel models

2008

A support vector domain method for change detection in multitemporal images

2010

This paper formulates the problem of distinguishing changed from unchanged pixels in multitemporal remote sensing images as a minimum enclosing ball (MEB) problem with changed pixels as target class. The definition of the sphere-shaped decision boundary with minimal volume that embraces changed pixels is approached in the context of the support vector formalism adopting a support vector domain description (SVDD) one-class classifier. SVDD maps the data into a high dimensional feature space where the spherical support of the high dimensional distribution of changed pixels is computed. Unlike the standard SVDD, the proposed formulation of the SVDD uses both target and outlier samples for defi…

An automatic filtering algorithm for SURF-based registration of remote sensing images

2017

International audience; The registration of remote sensing images has been often a necessary step for further analyses of images taken at different times, different viewing geometry or with different sensors. For this task there exists many approaches. This paper focuses on the feature-based category of image registration methods. Particularly, we propose an improvement of the SURF algorithm on the point matching step. Indeed, in order to achieve a correct registration, a good matching of feature point is required. However The presence of outliers lead to a fail in the registration. Therefore, in this paper, we introduce an efficient method devoted to the detection and removal of such outli…

Two optimizing procedures for the solution of complex systems of equations: a powerful tool for modelling and simulation of metabolism

2000

Introduction Standard calculations for the evaluation of indirect calorimetry (IC) are based on two-dimensional nonlinear systems of equations. For a more sophisticated evaluation metabolic models can be used, which are described by complex systems of equations. Since the solutions are multidimensional, a concrete result must be selected by means of constraints, using optimizing procedures. These multidimensional optimizations are critical concerning processing time and reproducibility of minimum detection. Methods In order to simulate the status of metabolism of ICU patients on the basis of IC data, a complex model of metabolism was developed. The model was described by a system of equatio…

Classification of SD-OCT Volumes for DME Detection: An Anomaly Detection Approach

2016

International audience; Diabetic Macular Edema (DME) is the leading cause of blindness amongst diabetic patients worldwide. It is characterized by accumulation of water molecules in the macula leading to swelling. Early detection of the disease helps prevent further loss of vision. Naturally, automated detection of DME from Optical Coherence Tomography (OCT) volumes plays a key role. To this end, a pipeline for detecting DME diseases in OCT volumes is proposed in this paper. The method is based on anomaly detection using Gaussian Mixture Model (GMM). It starts with pre-processing the B-scans by resizing, flattening, filtering and extracting features from them. Both intensity and Local Binar…