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Extended Poisson process modelling of dilution series data

机译:稀释系列数据的扩展Poisson过程建模

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摘要

Data comprising colony counts, or a binary variable representing fertile (or sterile) samples, as a dilution series of the containing medium are analysed by using extended Poisson process modelling. These models form a class of flexible probability distributions that are widely applicable to count and grouped binary data. Standard distributions such as Poisson and binomial, and those representing overdispersion and underdispersion relative to these distributions can be expressed within this class. For all the models in the class, likelihoods can be obtained. These models have not been widely used because of the perceived difficulty of performing the calculations and the lack of associated software. Exact calculation of the probabilities that are involved can be time consuming although accurate approximations that use considerably less computational time are available. Although dilution series data are the focus here, the models are applicable to any count or binary data. A benefit of the approach is the ability to draw likelihood-based inferences from the data.
机译:通过使用扩展的泊松过程建模,可以分析包含菌落计数或代表可育(或无菌)样品的二元变量(作为包含培养基的稀释系列)的数据。这些模型形成了一类灵活的概率分布,可广泛应用于计数和分组二进制数据。可以在此类中表示标准分布,例如泊松和二项式,以及代表相对于这些分布的过度分散和欠分散的分布。对于该类中的所有模型,都可以获得可能性。由于执行计算的困难和缺少相关软件,这些模型尚未得到广泛使用。精确计算所涉及的概率可能会很耗时,尽管可以使用使用更少计算时间的精确近似值。尽管稀释系列数据是这里的重点,但是这些模型适用于任何计数或二进制数据。该方法的优点是能够从数据中得出基于似然性的推断。

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