gl1ce
From lasso2 v1.2-9
by Berwin Turlach
Generalized Regression With L1-constraint on the Parameters
Fit a generalized regression problem while imposing an L1 constraint on
the parameters. Returns an object of class gl1ce
.
- Keywords
- models, regression
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, ...)
## S3 method for class 'gl1ce':
family(object, \dots)
Value
an object of class gl1ce
is returned by gl1ce()
.
See gl1ce.object
for details.
References
See the references in l1ce
.
Justin Lokhorst (1999).
The LASSO and Generalised Linear Models,
Honors Project, Nov.1999, Dept.Statist., Univ. of Adelaide.
Available as file
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)
sg1c
## Another comparison glm() / gl1c.E:
plot(predict(glm.E, type="link"), predict(glm.E, type="response"),
xlim = c(-3,0))
points(predict(gl1c.E, type="link"), predict(gl1c.E, type="response"),
col = 2, cex = 1.5)labels(gl1c.E)#-- oops! empty!!
Community examples
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