Somatic cell count is an accepted indicator of mastitis. However, measurements of cell count are subject to noise and outliers, which decrease their potential use in decision support. Statistical tools to separate noise from biologically relevant changes can help improving the interpretation of somatic cell count (SCC) data. The extension (Smith and West, 1983) of the multiprocess Kalmanfilter (Harrison and Stevens, 1976) to provide probabilities of different kinds of changes may be used in decision support - for example an action of treatment should be taken if the probability of an increase in SCC is above a critical level. The purpose of this presentation is to introduce dynamic linear model and in particular multiprocess class II mixture models with the recursive updating procedure for providing probabilities of different kinds of changes.
Proceedings of the World Congress on Genetics Applied to Livestock Production, Volume 2002. Session 16, , 16.13, 2002
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