In many contexts it is useful to predict the number of individuals in some population who will initiate a particular activity during a given period. For example, the number of users who will install a software update, the number of customers who will use a new feature on a website or who will participate in an A/B test. In practical settings, there is heterogeneity amongst individuals with regard to the distribution of time until they will initiate. For these reasons it is inappropriate to assume that the number of new individuals observed on successive days will be identically distributed. Given observations on the number of unique users participating in an initial period, we present a simple but novel Bayesian method for predicting the number of additional individuals who will participate during a subsequent period. We illustrate the performance of the method in predicting sample size in online experimentation.

翻译：在很多情况下,有必要预测某些人口中在某一时期将发起某项特定活动的人数,例如,将安装软件更新的用户人数、在网站上使用新功能或将参加A/B测试的客户人数。在实际情况下,个人之间在时间分配上存在差异,直到他们开始活动。由于这些原因,不适宜假定连续几天观察到的新人数将分布相同。根据对初始阶段参加的独特用户人数的意见,我们提出了一个简单但新颖的贝叶斯方法,用于预测以后一段时期将参加活动的更多人的数目。我们举例说明了在线实验中预测样本规模的方法的绩效。