对数学不是很精通,所以问个低级的关于特征向量的问题。运行附在最后面的程序,得到的结果如附在最后面的结果所示。
实际上,smf应该是矩阵
1 0 0
0 1 0
0 0 1
由于误差出现了
> smf
[,1] [,2] [,3]
[1,] 1.000000e+00 3.330669e-16 5.551115e-17
[2,] -7.401487e-17 1.000000e+00 -4.996004e-16
[3,] 1.060880e-15 1.554312e-15 1.000000e+00
再求它的特征值与特征向量,与矩阵
1 0 0
0 1 0
0 0 1
相比,特征值是一致的,但特征向量的区别很大,两个特征向量分别如下所示,so想问问这种区别是正常的么?特征向量能不能用呢?
[,1] [,2] [,3]
[1,] 0 0 1
[2,] 0 1 0
[3,] 1 0 0
$vectors
[,1] [,2] [,3]
[1,] 0.2592065 0.8079332 -0.5292031
[2,] 0.7595129 -0.5089880 -0.4050573
[3,] 0.5966173 0.2969431 0.7455687
程序:
f<-array(c(2,3,5,1,3,5,5,3,2),dim=c(3,3))
smf<-f%*%solve(f)
smf
eigen(smf)
eigen(array(c(1,0,0,0,1,0,0,0,1),dim=c(3,3)))
结果:
> f<-array(c(2,3,5,1,3,5,5,3,2),dim=c(3,3))
> smf<-f%*%solve(f)
> smf
[,1] [,2] [,3]
[1,] 1.000000e+00 3.330669e-16 5.551115e-17
[2,] -7.401487e-17 1.000000e+00 -4.996004e-16
[3,] 1.060880e-15 1.554312e-15 1.000000e+00
> eigen(smf)
$values
[1] 1 1 1
$vectors
[,1] [,2] [,3]
[1,] 0.2592065 0.8079332 -0.5292031
[2,] 0.7595129 -0.5089880 -0.4050573
[3,] 0.5966173 0.2969431 0.7455687
> eigen(array(c(1,0,0,0,1,0,0,0,1),dim=c(3,3)))
$values
[1] 1 1 1
$vectors
[,1] [,2] [,3]
[1,] 0 0 1
[2,] 0 1 0
[3,] 1 0 0