R: Do a lm on top of a lasso regression.

compute_gauss_lasso {PhylogeneticEM} | R Documentation

## Do a lm on top of a lasso regression.

### Description

`compute_gauss_lasso` takes the variables selected by a lasso procedure, and uses them to do a simple linear least square regression. Function used is `lm` for non-transformed data (root = NULL), and `lm.fit` for transformed data (root = an integer).

### Usage

    compute_gauss_lasso(Ypt, Xp, delta, root, projection = which(rowSums(delta) !=
      0))

### Arguments

`Xp` | (transformed) matrix of regression
`delta` | regression coefficients obtained with a lasso regression
`root` | the position of the root (intercept) in delta
`Yp` | (transformed) data

### Details

Depending on the value of root, the behavior is different. If root is null, then we fit a linear regression with an intercept. If root is equal to an integer, then the "intercept" column of the matrix Xp (that has possibly been trough a multiplication with a Cholesky decomposition of the variance) is included, rather than the intercept.

### Value

Named list, with "E0.gauss" the intercept (value at the root); "shifts.gauss" the list of shifts found on the branches; and "residuals" the residuals of the regression

[Package PhylogeneticEM version 1.1.0 Index]