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| 判别分析——二次型判别分析法 |
| Liu Huigang1,Hu Chunyan2, Hu Liangping2,3*(1. School of Basic Medical Sciences, Capital Medical University, Beijing 100069,China; |
| 投稿时间：2025-02-20 修订日期：2025-02-20 |
| DOI： |
| 中文关键词: 判别分析——二次型判别分析法 |
| 英文关键词:判别分析——二次型判别分析法 |
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| 中文摘要: |
| 【】本文目的是介绍与二次型判别分析有关的基本概念、计算方法、两个实例及其用SAS实现计算的方法。基本概念包括“二次型判别函数”“协方差矩阵”“贝叶斯判别准则”“Fisher判别准则”和“距离判别准则”；计算方法涉及“问题背景”“判别函数的形式”“判别规则”和“具体计算步骤”；两个实例中的资料分别是“五类作物在4个定量指标上的测定结果”和“四种麦子在8个定量指标上的测定结果”；借助SAS软件,对两个实例中的数据进行二次型判别分析,进而分别给出回代判别和基于刀切法进行交叉验证的总误判率。 |
| 英文摘要: |
| 【】The purpose of this article was to introduce the basic concepts, computational methods, two examples, and their implementation in SAS for quadratic discriminant analysis. The basic concepts included "quadratic discriminant function," "covariance matrix," "Bayesian discriminant criterion," "Fisher’s discriminant criterion," and "distance discriminant criterion. " The computational methods involved "problem background" "form of the discriminant function" "discriminant rules" and "specific steps of calculation" The data in the two examples were "measurement results of five types of crops on four quantitative indicators" and "measurement results of four types of wheat on eight quantitative indicators." Using SAS software, a quadratic discriminant analysis was performed on the data from both examples, and then the overall misclassification rates for resubstitution discrimination and cross-validation based on the jackknife method were provided respectively. |
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