gforce.Gamma: Estimates Gamma for the PECOK SDP.

In GFORCE: Clustering and Inference Procedures for High-Dimensional Latent Variable Models

Description

In particular, it returns in diagonal form the estimator Γ used to construct the PECOK penalized covariance estimator.

Usage

gforce.Gamma(X, par = FALSE, fast_estimator = FALSE, R_only = FALSE)

Arguments

X	n x d matrix. Each row represents a realization of a d dimensional random vector.
par	logical expression. If par == TRUE, then a multi-threaded version of the function is called. If par == FALSE, a single-threaded version is called.
fast_estimator	logical expression. If fast_estimator == TRUE, then the alternative estimator for \hat Γ is used.
R_only	logical expression. If R_only == TRUE, then no native code is run. If fast_estimator != TRUE this is ignored.

Value

The estimator Γ as a d dimensional numeric vector.

References

F. Bunea, C. Giraud, M. Royer and N. Verzelen. PECOK: a convex optimization approach to variable clustering. arXiv:1606.05100, 2016.

Examples

dat <- gforce.generator(5,20,20,3)
gam_hat <- gforce.Gamma(dat$X)

GFORCE documentation built on May 2, 2019, 3:44 a.m.