论刑事证据的概率分析

The probabilistic analysis of criminal evidence

证据分析的概率方法主要有客观概率分析、条件概率分析和模糊概率分析。证据的概率分析是多种方法综合应用的过程。在客观概率分析之下直接证据越多越容易认定案件事实,间接证据越多越不容易认定案件事实,而当单个证据的证明力不足时需要其他证据进行“质补”和“量补”才可能达到证明标准。条件概率指出证据的证明力不是孤立的,会随新证据的出现而变化。这种方法能够缓解客观概率分析的某些风险,但在先验概率赋值问题上存在难以克服的困难。客观概率分析和条件概率分析在一定程度上可以说明待证事实本身存在的可能性,却无力说明法官为什么相信待证事实存在。后者正是模糊概率分析解决的问题,其使用“隶属度”概念将“证据为真”转换为“相信为真”,为法官内心确信提供概率论基础。

The probabilistic analysis of evidence mainly includes objective probability analysis,conditional probability analysis and fuzzy probability analysis.Probabilistic analysis of evidence involves a comprehensive application of multiple methods.Under the objective probability analysis,the more direct evidence,the easier it is to ascertain the facts of the case,the more circumstantial evidence,the harder it is to ascertain the facts of the case.When the probative value of a single piece of evidence is insufficient,the standard of proof requires additional evidence,which plays the role of"quality supplement"or"quantity supplement".Conditional probability holds that the probative value of evidence is not isolated and will change as new evidence emerges.This method can mitigate some risk of error existing in objective probability analysis,but the insurmountable difficulties exist in the value assignment of probandum probabilities.Objective probability analysis and conditional probability analysis,to some extent,can explain the possibility of the existence of the facts to be proved,but they are unable to explain why judges believe that the facts exist.It is fuzzy probability analysis which solves the latter problem.It uses the concept of"membership"to convert"evidence is true"into"belief is true".This method provides a probabilistic basis for a judge's inner conviction.