Family oral fluids (FOFs) are an aggregate sample type shown to be a cost-efficient and convenient option for determining the porcine reproductive and respiratory syndrome virus (PRRSV) status of weaning age pigs. This study investigates the effect of pooling PRRSV-positive FOF samples with PRRSV-negative FOF samples at different levels (1/3, 1/5, 1/10, 1/20) on the probability of PRRSV RNA detection by reverse-transcription real-time polymerase chain reaction (RT-rtPCR). Mathematical models were built to assess how much the probability of RT-rtPCR PRRSV detection changed with increasing proportion of PRRSV-positive samples present within pools and how partially sampling a farrowing room influenced the probability of RT-rtPCR detection of PRRSV RNA in pooled samples at different prevalence scenarios.
View Article and Find Full Text PDFWe use observed transmission line outage data to make a Markovian influence graph that describes the probabili- ties of transitions between generations of cascading line outages. Each generation of a cascade consists of a single line outage or multiple line outages. The new influence graph defines a Markov chain and generalizes previous influence graphs by including multiple line outages as Markov chain states.
View Article and Find Full Text PDFStat (Int Stat Inst)
January 2018
Clustering partitions a dataset such that observations placed together in a group are similar but different from those in other groups. Hierarchical and -means clustering are two approaches but have different strengths and weaknesses. For instance, hierarchical clustering identifies groups in a tree-like structure but suffers from computational complexity in large datasets while -means clustering is efficient but designed to identify homogeneous spherically-shaped clusters.
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