regression - R: Error in lars(x = , y = , type = "lasso") -

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i trying run lasso (least absolute shrinkage , selection operator) using lars package in r. here dimension of data:

dim(y) : 235 50

dim(x) : 235 15

when running following:

 library(lars)  return = as.matrix(ret.ff.zoo)   ### "y"  data = as.matrix(df)   ### "x"  lasso <- lars(data, return, type = c("lasso"))

i following error:

 > lasso <- lars(data, return, type = c("lasso"))   error in cvec - gamhat * gram[, active, drop = false] %*% w :     non-conformable arrays

when make response variable "y" vector, follows:

 lasso <- lars(data, return[,1], type = c("lasso"))

it works! however, doing means lasso performed on 1 security out of 3000 panel. how can formula extended analyze panel of data?? doing lasso separately on each of 3000 securities doesn't make sense excludes cross-sectional dynamic.

i use can get! thanks!


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