无限过程的内在性、传递和无穷小建模
Internality, transfer, and infinitesimal modeling of infinite processes
摘要：
当没有合理的理由指定一个特定的无穷小值作为单个事件的概率时，概率模型是欠定的。Pruss声称超现实概率是欠定的。该索赔是基于外部超实值的措施。我们证明了内部超有限测度不是欠定的。内在性的重要性源于罗宾逊的转移原则只适用于内部实体的事实。我们还评估的索赔，transferless序域（超现实，列维Civita字段，洛朗级数）可能有优势超现实概率建模。我们表明，在这样的领域发展的概率是表达比超现实概率。
英文摘要：
A probability model is underdetermined when there is no rational reason to assign a particular infinitesimal value as the probability of single events. Pruss claims that hyperreal probabilities are underdetermined. The claim is based upon external hyperreal-valued measures. We show that internal hyperfinite measures are not underdetermined. The importance of internality stems from the fact that Robinson's transfer principle only applies to internal entities. We also evaluate the claim that transferless ordered fields (surreals, Levi-Civita field, Laurent series) may have advantages over hyperreals in probabilistic modeling. We show that probabilities developed over such fields are less expressive than hyperreal probabilities.
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