lars (version 1.1)

predict.lars: Make predictions or extract coefficients from a fitted lars model

Description

While lars() produces the entire path of solutions, predict.lars allows one to extract a prediction at a particular point along the path.

Usage

## S3 method for class 'lars':
predict(object, newx, s, type = c("fit", "coefficients"), mode = c("step", 
    "fraction", "norm", "lambda"), ...)
## S3 method for class 'lars':
coef(object, ...)

Value

Either a vector/matrix of fitted values, or a vector/matrix of coefficients.

Details

LARS is described in detail in Efron, Hastie, Johnstone and Tibshirani (2002). With the "lasso" option, it computes the complete lasso solution simultaneously for ALL values of the shrinkage parameter in the same computational cost as a least squares fit.

References

Efron, Hastie, Johnstone and Tibshirani (2002) "Least Angle Regression" (with discussion) Annals of Statistics; see also http://www-stat.stanford.edu/~hastie/Papers/LARS/LeastAngle_2002.pdf. Hastie, Tibshirani and Friedman (2002) Elements of Statistical Learning, Springer, NY.

See Also

print, plot, lars, cv.lars

Examples

data(diabetes)
attach(diabetes)
object <- lars(x,y,type="lasso")
### make predictions at the values in x, at each of the
### steps produced in object
fits <- predict.lars(object, x, type="fit")
### extract the coefficient vector with L1 norm=4.1
coef4.1 <- coef(object, s=4.1, mode="norm") # or
coef4.1 <- predict(object, s=4.1, type="coef", mode="norm")
detach(diabetes)