Description Usage Arguments Value Examples
Fit the desparsified lasso presmoothing estimator with cubic B-splines
1 | spadd.presmth.Bspl(X, Y, d.pre, lambda, eta, n.foi)
|
X |
the design matrix |
Y |
the response vector (centered) |
d.pre |
the number of intervals in which to divide the support of each covariate |
lambda |
the tuning parameter for fitting the group lasso estimate for the bias correction |
eta |
the tuning parameter for the group lasso projection of one set of basis functions onto those of the other covariates. |
n.foi |
the number of functions (first columns of |
a list with the fitted functions etc.
1 2 3 4 5 6 7 8 9 10 11 12 | data <- data_gen(n = 200, q = 10, r = .5)
spadd.presmth.Bspl.out <- spadd.presmth.Bspl(X = data$X,
Y = data$Y,
d.pre = 20,
lambda = 1,
eta = 3,
n.foi = 6)
plot_presmth_Bspl(spadd.presmth.Bspl.out,
true.functions = list( f = data$f,
X = data$X))
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.