Decomposition of Prediction Error
Decomposition of Prediction Error
复制标题
预测误差分解
DOI：
10.1080/01621459.1985.10477152
复制
发表时间：
1985
影响因子：
3.7
通讯作者：
D. Harville
中科院分区：
文献类型：
--
作者：
D. Harville
本文考虑的问题是从可观测的随机向量y的值预测不可观测的随机变量w的值。这个问题被认为是在四种状态下的知识的联合分布的w和y，从完整的知识到“没有”的知识。为每个案例提供了一个或多个（点）预测因子。预测误差被分解，以便每个分量反映信息的缺失。在某些条件下，这些分量是不相关的，并且具有零均值。给出了各分量方差的精确或近似表达式。
Abstract The problem considered is that of predicting the value of an unobservable random variable w from the value of an observable random vector y. This problem is considered under each of four states of knowledge about the joint distribution of w and y, ranging from complete knowledge to “no” knowledge. A (point) predictor or predictors are presented for each case. Prediction error is decomposed so that each component reflects an absence of information. Under certain conditions, these components are uncorrelated and have zero means. An exact or approximate expression is given for the variance of each component.