Sorry, resending with correct subject line.
I didn't find the development version of your package but the latest version
archived on CRAN uses Rcpp, RcppArmadillo.
Since the latest versions of Rcpp and Armadillo support registration, it may be
something related to RcppAttributes() or similar. I
I didn't find the development version of your package but the latest version
archived on CRAN uses Rcpp, RcppArmadillo.
Since the latest versions of Rcpp and Armadillo support registration, it may be
something related to RcppAttributes()
or similar. I think that you don't need to do registration
I am attempting to use the lars package with a sparse input feature matrix,
but the following fails:
library(Matrix)
library(lars)
data(diabetes)
attach(diabetes)
x = as(as.matrix(as.data.frame(x)), 'dgCMatrix')
lars(x, y, intercept = FALSE)
Error in scale.default(x, FALSE, normx) :
>
> length