实施贝叶斯预测程序：K-素数和K-平方分布
Implementing Bayesian predictive procedures: The K-prime and K-square distributions
摘要：
标准正态模型下的贝叶斯预测程序的实施。有两个分布是特别有趣的，K-素数和K-平方分布。它们也给出了简单和多重相关系数的精确推论。它们的累积分布函数可以用不完全贝塔函数比的无穷级数表示，因而适于递归计算。提供了有效的算法。为了处理特殊情况下，可能的下溢可能会阻止正常工作的复发，提出了一个简单的解决方案，导致在两类算法之间的过程。给出了一些应用实例。
英文摘要：
The implementation of Bayesian predictive procedures under standard normal models is considered. Two distributions are of particular interest, the K-prime and K-square distributions. They also give exact inferences for simple and multiple correlation coefficients. Their cumulative distribution functions can be expressed in terms of infinite series of multiples of incomplete beta function ratios, thus adequate for recursive calculations. Efficient algorithms are provided. To deal with special cases where possible underflows may prevent a recurrence to work properly, a simple solution is proposed which results in a procedure which is intermediate between two classes of algorithm. Some examples of applications are given.
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