summary(CA) ## 绘图数据提取 ## 绘图数据提取 s.CA=CA$CA$u # 提取样本特征值 s.CA e.CA=CA$CA$v # 提取物种特征值 e.CA # 可执行选取排序轴绘制散点图 图10|CA描述统计结果。 3.5 CCA # vegan::cca()函数,加环境因子就是CCA分析 CCA=cca(spe,env) CCA summary(CCA) ## 绘图数据提取 s....
summary(pc) # 1 component has > 99% variance loadings(pc) # Can see all variance is in the range in miles Importance of components: Comp.1 Comp.2 Comp.3 Comp.4Standard deviation 2259.2372556 6.907940e+01 2.871764e+01 2.259929e+01Proportion of Variance 0.9987016 9.337038e-04 1.613651e-04 ...
R - SE: model_summary - use algorithm from model_id if present, if not… 4年前 h2o-samples/src/main/java/droplets Refactor K-Means output: rename rows -> size. 10年前 h2o-security [SW-7318] Make generateSSLPair public to avoid duplication on Sparklin… 5年前 h2o-test-accurac...
0611 16:11 pca<-function(matr,scla=TRUE){respca<-summary(prcomp(matr,scale=scl))n<-nrow(matr)if(scla){respca$loadings<-t(respca$sdev*t(respca$rotation))}else{respca$loadings<-t(respca$sdev*t(respca$rotation))/apply(matr,2,sd)}respca$loadings[is.nan(respca$loadings)]<-0return...