sas学习的代码.zip

[{"title":"（ 16 个子文件 320KB ） sas学习的代码.zip","children":[{"title":"sasѧϰ","children":null,"spread":false},{"title":"sas学习","children":[{"title":"判别分析","children":[{"title":"逐步判别分析.txt <span style='color:#111;'> 1.21KB </span>","children":null,"spread":false},{"title":"一般判别分析.txt <span style='color:#111;'> 992B </span>","children":null,"spread":false},{"title":"典型判别分析.txt <span style='color:#111;'> 905B </span>","children":null,"spread":false}],"spread":true},{"title":"因子分析","children":[{"title":"因子分析.txt <span style='color:#111;'> 2.58KB </span>","children":null,"spread":false}],"spread":true},{"title":"主成分分析法","children":[{"title":"主成分分析.txt <span style='color:#111;'> 1.94KB </span>","children":null,"spread":false}],"spread":true},{"title":"时间序列模型","children":[{"title":"proc arima.docx <span style='color:#111;'> 321.68KB </span>","children":null,"spread":false},{"title":"时间序列模型.txt <span style='color:#111;'> 2.10KB </span>","children":null,"spread":false}],"spread":true},{"title":"回归分析","children":[{"title":"一元线性回归.txt <span style='color:#111;'> 572B </span>","children":null,"spread":false},{"title":"logistc回归.txt <span style='color:#111;'> 2.12KB </span>","children":null,"spread":false},{"title":"相关分析.txt <span style='color:#111;'> 378B </span>","children":null,"spread":false},{"title":"多元线性回归.txt <span style='color:#111;'> 354B </span>","children":null,"spread":false},{"title":"非线性回归分析.txt <span style='color:#111;'> 908B </span>","children":null,"spread":false},{"title":"逐步回归分析.txt <span style='color:#111;'> 814B </span>","children":null,"spread":false}],"spread":true},{"title":"聚类分析","children":[{"title":"快速聚类.txt <span style='color:#111;'> 3.47KB </span>","children":null,"spread":false},{"title":"系统聚类分析(1).txt <span style='color:#111;'> 3.50KB </span>","children":null,"spread":false},{"title":"变量聚类.txt <span style='color:#111;'> 2.93KB </span>","children":null,"spread":false}],"spread":true}],"spread":true}],"spread":true}]