jmlr06data {qp}R Documentation

Synthetic data from the article by Castelo and Roverato (2006)

Description

Synthetic data generated from two graphs with 150 vertices, $G_1$ and $G_2$. In $G_1$ the boundary of every vertex is at most 5, while in $G_2$ the boundary of every vertext is at most 20

Usage

data(jmlr06data)

Format

IC.bd5: inverse correlation matrix encoding the independence structure of $G_1$
IC.bd20: inverse correlation matrix encoding the independence structure of $G_2$
S.bd5.N20: sample covariance matrix from a sample of size 20 drawn from a normal
distribution with mean 0 and inverse correlation matrix IC.bd5
S.bd5.N50: sample covariance matrix from a sample of size 50 drawn from a normal
distribution with mean 0 and inverse correlation matrix IC.bd5
S.bd5.N150: sample covariance matrix from a sample of size 150 drawn from a normal
distribution with mean 0 and inverse correlation matrix IC.bd5
S.bd20.N20: sample covariance matrix from a sample of size 20 drawn from a normal
distribution with mean 0 and inverse correlation matrix IC.bd20
S.bd20.N50: sample covariance matrix from a sample of size 50 drawn from a normal
distribution with mean 0 and inverse correlation matrix IC.bd20
S.bd20.N150: sample covariance matrix from a sample of size 150 drawn from a normal
distribution with mean 0 and inverse correlation matrix IC.bd20
qp.out.bd5.N20.q10: output from qp.search applied to S.bd5.N20 with q=10 and T=500
qp.out.bd20.N20.q10: output from qp.search applied to S.bd20.N20 with q=10 and T=500

References

Castelo, R. and Roverato, A. (2006). A robust procedure for Gaussian graphical model search from microarray data with p larger than n, J. Mach. Learn. Res., 7:2621-2650


[Package qp version 0.3-1 Index]