Description Usage Arguments Details Author(s) References See Also Examples
Prints information and diagnostic statistics for a particular Liso fit.
1 2 |
x |
A |
Dummy variables for compatibility:
... |
Unused. |
print
prints, in this case, n, p, Lambda for the fit, and then for each non-zero fitted variable, stepwise and total variation complexity statistics, as well as the apparent monotonicity of the fit if it was not pre-specified. Finally some residual statistics are printed.
Zhou Fang
Zhou Fang and Nicolai Meinshausen (2009), Liso for High Dimensional Additive Isotonic Regression, available at http://blah.com
1 2 3 4 5 6 7 8 9 10 11 | ## Use the method on a simulated data set
set.seed(79)
n <- 100; p <- 50
## Simulate design matrix and response
x <- matrix(runif(n * p, min = -2.5, max = 2.5), nrow = n, ncol = p)
y <- scale(3 * (x[,1]> 0), scale=FALSE) + x[,2]^3 + rnorm(n)
## try lambda = 2
fits <- liso.backfit(x,y, 2)
print(fits)
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