l1ce

0th

Percentile

Regression Fitting With L1-constraint on the Parameters

Returns an object of class "l1ce" or "licelist" that represents fit(s) of linear models while imposing L1 constraint(s) on the parameters.

Keywords
models, regression, optimize
Usage
l1ce(formula, data = sys.parent(), weights, subset, na.action,
     sweep.out = ~ 1, x = FALSE, y = FALSE,
     contrasts = NULL, standardize = TRUE,
     trace = FALSE, guess.constrained.coefficients = double(p),
     bound = 0.5, absolute.t = FALSE)
Value

an object of class l1ce (if bound was a single value) or l1celist (if bound was a vector of values) is returned. See l1ce.object and l1celist.object for details.

References

Osborne, M.R., Presnell, B. and Turlach, B.A. (2000) On the LASSO and its Dual, Journal of Computational and Graphical Statistics 9(2), 319--337.

Tibshirani, R. (1996) Regression shrinkage and selection via the lasso, Journal of the Royal Statistical Society, Series B 58(1), 267--288.

Aliases
Examples
data(Iowa)
l1c.I <- l1ce(Yield ~ ., Iowa, bound = 10, absolute.t=TRUE)
l1c.I

## The same, printing information in each step:
l1ce(Yield ~ ., Iowa, bound = 10, trace = TRUE, absolute.t=TRUE)

data(Prostate)
l1c.P <- l1ce(lpsa ~ ., Prostate, bound=(1:30)/30)
length(l1c.P)# 30 l1ce models
l1c.P # -- MM: too large; should do this in summary(.)!
<testonly>str(l1c.P, max.lev = 1)</testonly>

plot(resid(l1c.I) ~ fitted(l1c.I))
abline(h = 0, lty = 3, lwd = .2)
Documentation reproduced from package lasso2, version 1.2-0, License: GPL version 2 or later

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