影响检验I：理想复合假设检验和因果半度量
Influence tests I: ideal composite hypothesis tests, and causal semimeasures
摘要：
研究了假设对应的普适可测半测度之比作为统计复合假设检验的一种解决方案，如果可以假设计算时间是无限的。利用广义结构方程定义了离散时间序列的影响检验。介绍了几种理想的测试，有人认为，当停止信息传输，在某些情况下，瞬时的原因和后果可以推断出这是不可能的经典。该方法与贝叶斯定义的影响，它是开放的，是否所有贝叶斯因果关联的通用半措施是一个常数内相等。最后，该方法还与现有的工程程序的影响和因果关系的理论定义进行了对比。
英文摘要：
Ratios of universal enumerable semimeasures corresponding to hypotheses are investigated as a solution for statistical composite hypotheses testing if an unbounded amount of computation time can be assumed. Influence testing for discrete time series is defined using generalized structural equations. Several ideal tests are introduced, and it is argued that when Halting information is transmitted, in some cases, instantaneous cause and consequence can be inferred where this is not possible classically. The approach is contrasted with Bayesian definitions of influence, where it is left open whether all Bayesian causal associations of universal semimeasures are equal within a constant. Finally the approach is also contrasted with existing engineering procedures for influence and theoretical definitions of causation.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
