Multivariate outlier detection of dairy herd testing data

Ho Chang Choi, Howard Paul Edwards, C Hassell Sweatman, V Obolonkin


This paper describes the challenge presented by the Livestock Improvement Corporation regarding the need to detect multivariate outliers in very large datasets of dairy herd milk testing data. Various approaches and techniques were applied to a subset of one dataset in order to establish the potential of both manual and automatic detection of outliers in large datasets using multivariate statistical techniques.

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statistics, multivariate statistics, outlier detection

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ANZIAM Journal, ISSN 1446-8735, copyright Australian Mathematical Society.