论文标题
无限过程的内在，传递和无限建模
Internality, transfer, and infinitesimal modeling of infinite processes
论文作者
论文摘要
当没有合理理由将特定的无限值分配为单个事件的概率时，概率模型就不确定。普鲁斯声称超新概率不确定。该索赔是基于外部超现实价值措施的。我们表明，内部高铁措施并不确定。内部性的重要性源于鲁滨逊的转移原则仅适用于内部实体。我们还评估了以下主张：无转移有序场（超现实，Levi-Civita Field，Laurent Series）可能比概率建模中的超现实具有优势。我们表明，在此类领域发展的概率不如超现实概率表达不足。
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.
