验证相关系数矩阵与标准化后协方差矩阵相等

验证相关系数矩阵与 标准 excel标准偏差excel标准偏差函数exl标准差函数国标检验抽样标准表免费下载红头文件格式标准下载 化后协方差矩阵相等 c=read.csv(file=file.choose(),head=T) > colmeans(c) 错误: 没有"colmeans"这个函数 > c1=c[1:3,1:3] > colMeans(c1) X1 X.2 X0 NA NA NA > c=read.csv(file=file.choose(),head=T) > c1=c[1:3,1:3] > c=read.csv(file=file.choose(),head=T) > c1=c[1:3,1:3] > colMeans(c1) x1 x2 x3 -0.3333333 1.0000000 0.6666667 > cov(c1) x1 x2 x3 x1 2.3333333 -5.5 0.3333333 x2 -5.5000000 13.0 -1.0000000 x3 0.3333333 -1.0 1.3333333 > cor(c1) x1 x2 x3 x1 1.0000000 -0.9986254 0.1889822 x2 -0.9986254 1.0000000 -0.2401922 x3 0.1889822 -0.2401922 1.0000000 > eigen(c1) $values [1] 5.8284271 2.0000000 0.1715729 $vectors [,1] [,2] [,3] [1,] -0.3826834 0 0.9238795 [2,] 0.9238795 0 0.3826834 [3,] 0.0000000 1 0.0000000 > c=read.csv(file=file.choose(),head=T) > c1=c[1:3,1:3] > scale(c1) x1 x2 x3 1 0.7657533 -0.9215278 0.07900694 2 -1.1313527 -0.1418054 -1.03715994 3 0.3655994 1.0633333 0.95815300 attr(,"scaled:center") x1 x2 x3 0.09738030 0.03099798 0.11949950 attr(,"scaled:scale") x1 x2 x3 0.07460766 0.01956018 0.06527684 > c=read.csv(file=file.choose(),head=T) > c1=c[1:3,1:3] > > colMeans(c1) x1 x2 x3 4 5 6 > cov(c1) x1 x2 x3 x1 9 9 9 x2 9 9 9 x3 9 9 9 > cor(c1) x1 x2 x3 x1 1 1 1 x2 1 1 1 x3 1 1 1 > c=read.csv(file=file.choose(),head=T) > c1=c[1:3,1:3] > scale(c1) x1 x2 x3 1 -1 -1 -1 2 0 0 0 3 1 1 1 attr(,"scaled:center") x1 x2 x3 4 5 6 attr(,"scaled:scale") x1 x2 x3 3 3 3 > c2=scale(c1) > colMeans(c2) x1 x2 x3 0 0 0 > cov(c2) x1 x2 x3 x1 1 1 1 x2 1 1 1 x3 1 1 1 > cor(c2) x1 x2 x3 x1 1 1 1 x2 1 1 1 x3 1 1 1 > c=read.csv(file=file.choose(),head=T) > c1=c[1:3,1:3] > ) 错误: 意外的')'在")"里 > colMeans(c1) x1 x2 x3 8.666667 5.666667 5.333333 > cov(c1) x1 x2 x3 x1 32.333333 -16.666667 -7.333333 x2 -16.666667 10.333333 7.666667 x3 -7.333333 7.666667 10.333333 > cor(c1) x1 x2 x3 x1 1.0000000 -0.9118078 -0.4011954 x2 -0.9118078 1.0000000 0.7419355 x3 -0.4011954 0.7419355 1.0000000 > scale(c1) x1 x2 x3 1 1.1137997 -1.1406469 -0.7258662 2 -0.8206945 0.4147807 -0.4147807 3 -0.2931052 0.7258662 1.1406469 attr(,"scaled:center") x1 x2 x3 8.666667 5.666667 5.333333 attr(,"scaled:scale") x1 x2 x3 5.686241 3.214550 3.214550 > c2=scale(c1) > colMeans(c2) x1 x2 x3 9.251859e-17 -1.480297e-16 1.480297e-16 > cov(c2) x1 x2 x3 x1 1.0000000 -0.9118078 -0.4011954 x2 -0.9118078 1.0000000 0.7419355 x3 -0.4011954 0.7419355 1.0000000 > cor(c2) x1 x2 x3 x1 1.0000000 -0.9118078 -0.4011954 x2 -0.9118078 1.0000000 0.7419355 x3 -0.4011954 0.7419355 1.0000000 > c=read.csv(file=file.choose(),head=T) > colmeans(c) 错误: 没有"colmeans"这个函数 > c1=c[1:3,1:3] > colMeans(c1) X1 X.2 X0 NA NA NA > c=read.csv(file=file.choose(),head=T) > c1=c[1:3,1:3] > c=read.csv(file=file.choose(),head=T) > c1=c[1:3,1:3] > colMeans(c1) x1 x2 x3 -0.3333333 1.0000000 0.6666667 > cov(c1) x1 x2 x3 x1 2.3333333 -5.5 0.3333333 x2 -5.5000000 13.0 -1.0000000 x3 0.3333333 -1.0 1.3333333 > cor(c1) x1 x2 x3 x1 1.0000000 -0.9986254 0.1889822 x2 -0.9986254 1.0000000 -0.2401922 x3 0.1889822 -0.2401922 1.0000000 > eigen(c1) $values [1] 5.8284271 2.0000000 0.1715729 $vectors [,1] [,2] [,3] [1,] -0.3826834 0 0.9238795 [2,] 0.9238795 0 0.3826834 [3,] 0.0000000 1 0.0000000 > c=read.csv(file=file.choose(),head=T) > c1=c[1:3,1:3] > scale(c1) x1 x2 x3 1 0.7657533 -0.9215278 0.07900694 2 -1.1313527 -0.1418054 -1.03715994 3 0.3655994 1.0633333 0.95815300 attr(,"scaled:center") x1 x2 x3 0.09738030 0.03099798 0.11949950 attr(,"scaled:scale") x1 x2 x3 0.07460766 0.01956018 0.06527684 > c=read.csv(file=file.choose(),head=T) > c1=c[1:3,1:3] > > colMeans(c1) x1 x2 x3 4 5 6 > cov(c1) x1 x2 x3 x1 9 9 9 x2 9 9 9 x3 9 9 9 > cor(c1) x1 x2 x3 x1 1 1 1 x2 1 1 1 x3 1 1 1 > c=read.csv(file=file.choose(),head=T) > c1=c[1:3,1:3] > scale(c1) x1 x2 x3 1 -1 -1 -1 2 0 0 0 3 1 1 1 attr(,"scaled:center") x1 x2 x3 4 5 6 attr(,"scaled:scale") x1 x2 x3 3 3 3 > c2=scale(c1) > colMeans(c2) x1 x2 x3 0 0 0 > cov(c2) x1 x2 x3 x1 1 1 1 x2 1 1 1 x3 1 1 1 > cor(c2) x1 x2 x3 x1 1 1 1 x2 1 1 1 x3 1 1 1 > c=read.csv(file=file.choose(),head=T) > c1=c[1:3,1:3] > ) 错误: 意外的')'在")"里 > colMeans(c1) x1 x2 x3 8.666667 5.666667 5.333333 > cov(c1) x1 x2 x3 x1 32.333333 -16.666667 -7.333333 x2 -16.666667 10.333333 7.666667 x3 -7.333333 7.666667 10.333333 > cor(c1) x1 x2 x3 x1 1.0000000 -0.9118078 -0.4011954 x2 -0.9118078 1.0000000 0.7419355 x3 -0.4011954 0.7419355 1.0000000 > scale(c1) x1 x2 x3 1 1.1137997 -1.1406469 -0.7258662 2 -0.8206945 0.4147807 -0.4147807 3 -0.2931052 0.7258662 1.1406469 attr(,"scaled:center") x1 x2 x3 8.666667 5.666667 5.333333 attr(,"scaled:scale") x1 x2 x3 5.686241 3.214550 3.214550 > c2=scale(c1) > colMeans(c2) x1 x2 x3 9.251859e-17 -1.480297e-16 1.480297e-16 > cov(c2) x1 x2 x3 x1 1.0000000 -0.9118078 -0.4011954 x2 -0.9118078 1.0000000 0.7419355 x3 -0.4011954 0.7419355 1.0000000 > cor(c2) x1 x2 x3 x1 1.0000000 -0.9118078 -0.4011954 x2 -0.9118078 1.0000000 0.7419355 x3 -0.4011954 0.7419355 1.0000000 >