psdr_bic {psvmSDR} | R Documentation |
Estimation of a structural dimensionality. Choose the k which maximizes a BIC (Bayesian information criterion) value.
psdr_bic(obj, rho = 0.01, plot = TRUE, ...)
obj |
The psdr object |
rho |
Parameter for BIC criterion. Default is 0.01. |
plot |
Boolean. If TRUE, the plot of BIC values are depicted. |
... |
Additional arguments to be passed to generic |
Estimated BIC scores for determining the optimal structural dimension will be returned with plot.
Jungmin Shin, jungminshin@korea.ac.kr, Seung Jun Shin, sjshin@korea.ac.kr, Andreas Artemiou artemiou@uol.ac.cy
Li, B., Artemiou, A. and Li, L. (2011) Principal support vector machines for linear and nonlinear sufficient dimension reduction, Annals of Statistics 39(6): 3182–3210.
set.seed(1234)
n <- 200; p <- 10;
x <- matrix(rnorm(n*p, 0, 1), n, p)
y <- x[,1]/(0.5 + (x[,2] + 1)^2) + rnorm(n, 0, .2)
obj <- psdr(x, y, loss="svm")
d.hat <- psdr_bic(obj)
print(d.hat)