matrix(rnorm(20*10),nrow=20,ncol=10)
> beta<-rep(0,10)
> for(i in 1:3){beta<-2}
> epsion<-rnorm(20)
> y<-x%*%beta+epsion
> aa<-lars(x,y,type="lar")
> coef(aa)
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 0.0000000 0.00000000 0.0000000 0.0000000 0.00000000 0.00000000 0.0000000 0.00000000 0.00000000 0.0000000
[2,] 0.0000000 0.04195032 0.0000000 0.0000000 0.00000000 0.00000000 0.0000000 0.00000000 0.00000000 0.0000000
[3,] 0.0000000 0.55708364 0.5451486 0.0000000 0.00000000 0.00000000 0.0000000 0.00000000 0.00000000 0.0000000
[4,] 0.8628391 1.30251374 1.3646600 0.0000000 0.00000000 0.00000000 0.0000000 0.00000000 0.00000000 0.0000000
[5,] 1.1557687 1.56559291 1.9207280 0.0000000 0.00000000 0.00000000 -0.4618920 0.00000000 0.00000000 0.0000000
[6,] 1.1960819 1.64183799 2.1076143 0.0000000 0.00000000 0.00000000 -0.5940158 0.00000000 0.00000000 -0.1374490
[7,] 1.1993646 1.64651190 2.1293001 0.0000000 0.00000000 -0.02164942 -0.6175903 0.00000000 0.00000000 -0.1528846
[8,] 1.2334462 1.66630236 2.2360097 0.0000000 0.00000000 -0.13497538 -0.7266663 0.08864167 0.00000000 -0.2386374
[9,] 1.2430027 1.66794420 2.2614039 0.0000000 0.00000000 -0.15615013 -0.7530509 0.10682223 0.01082718 -0.2558360
[10,] 1.3014877 1.67216087 2.3464883 0.0000000 0.06767723 -0.22527078 -0.8269592 0.16104165 0.06117901 -0.3243835
[11,] 1.2209966 1.62915975 2.6254595 -0.2609547 -0.08698971 -0.21113413 -0.9777476 0.24392155 0.18843636 -0.3891996
这个结果是什么意思啊？beta应该是一个向量啊
