lasso2 (version 1.0-1)

gl1ce: Generalized Regression With L1-constraint on the Parameters

Description

Fit a generalized regression problem while imposing an L1 constraint on the parameters. Returns an object of class gl1ce.

Usage

gl1ce(formula, data = sys.parent(), weights, subset, na.action,
      family = gaussian, control = glm.control(...), sweep.out = ~ 1,
      x = FALSE, y = TRUE, contrasts = NULL, standardize = TRUE,
      guess.constrained.coefficients = double(p), bound = 0.5, ...)

Value

an object of class gl1ce is returned. See gl1ce.object for details.

See Also

glm for unconstrained generalized regression modeling.

Examples

## example from base:
data(esoph)
summary(esoph)
## effects of alcohol, tobacco and interaction, age-adjusted
modEso <- formula(cbind(ncases, ncontrols) ~ agegp + tobgp * alcgp)
glm.E   <- glm(modEso, data = esoph, family = binomial())
gl1c.E <- gl1ce(modEso, data = esoph, family = binomial())
gl1c.E
plot(residuals(gl1c.E) ~ fitted(gl1c.E))

sg1c <- summary(gl1c.E)
sg1clabels(gl1c.E)#-- oops! empty!!