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Showing 1 to 5 of 5 for “"Multivariate Outliers"”.
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Profile Monitoring for Mixed Model Data
… parameter estimators within a general context of multivariate quality control. The goal of Phase I analysis of multivariate quality control data is to identify multivariate outliers and step changes so that the estimated control limits are sufficiently accurate for Phase II monitoring. High …
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Multivariate Outlier Mining Using Cluster Analysis: Case Study - National Health Interview Survey
… in many statistical analyses, especially in multivariate cases. Outliers may exert undue influence on outcomes of the analysis. In most cases, it is a big challenge to reveal the pattern of the outliers and the "outlyingness". There are several approaches and methods to detect anomalous data …
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Cluster-Based Bounded Influence Regression
… may be unable to combat a small percentage of outliers. A high-breakdown procedure such as least trimmed squares (LTS) regression can accommodate up to 50% of the data (in the limit) being outlying with respect to the general trend. Two available one-step improvement procedures based on LTS are …
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The Effects of IS-BAO Implementation and Leadership Performance on Safety Culture in Business Aviation Flight Operations
… 846 were usable and 771 actually used after multivariate outliers were removed. Confirmatory factor analyses verified the safety culture perceptions construct and factor loading on Bolman and Deal’s frames and demonstrated convergent and discriminant validity. Structural equation model (SEM) …
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Cluster_Based Profile Monitoring in Phase I Analysis
… process is equivalent to the detection of multivariate outliers. For this reason, we also compared our proposed method to a popular method used to identify outliers when dealing with a multivariate response. Our study demonstrated that when the out-of-control process corresponds to a …