HDPenReg (version 0.94.9)

HDfusion: Fusion algorithm

Description

It performs the lars algorithm for solving a special case of lasso problem. It is a linear regression problem with a l1-penalty on the difference of two successive coefficients.

Usage

HDfusion(
  X,
  y,
  maxSteps = 3 * min(dim(X)),
  intercept = TRUE,
  eps = .Machine$double.eps^0.5
)

Value

An object of type LarsPath. LarsPath-class.

Arguments

X

the matrix (of size n*p) of the covariates.

y

a vector of length n with the response.

maxSteps

Maximal number of steps for lars algorithm.

intercept

If TRUE, there is an intercept in the model.

eps

Tolerance of the algorithm.

Author

Quentin Grimonprez

References

Efron, Hastie, Johnstone and Tibshirani (2003) "Least Angle Regression" (with discussion) Annals of Statistics

See Also

LarsPath HDlars

Examples

set.seed(10)
dataset <- simul(50, 10000, 0.4, 10, 50, matrix(c(0.1, 0.8, 0.02, 0.02), nrow = 2))
result <- HDfusion(dataset$data, dataset$response)