Description Usage Arguments Details Value Author(s) References Examples
To compute an equvalent mearsure of partial correlation coeffients called ψ scores.
1 | psical(iData,iMaxNei,ALPHA1=0.05,GRID=2,iteration=100)
|
iData |
a nxp data matrix. |
iMaxNei |
Neiborhood size in correlation screening step, default to n/log(n), where n is the number of observation. |
ALPHA1 |
The significance level of correlation screening. In general, a high significance level of correlation screening will lead to a slightly large separator set S_{ij}, which reduces the risk of missing some important variables in the conditioning set. Including a few false variables in the conditioning set will not hurt much the accuracy of the ψ-partial correlation coefficient. |
GRID |
The number of components for the corrlation scores. The default value is 2. |
iteration |
Number of iterations for screening. The default value is 100. |
This is the function to calculate ψ scores and can be used in combining or detecting difference of two networks.
score |
Estimated ψ score matrix which has 3 columns. The first two columns denote the pair indices of variables i and j and the last column denote the calculated ψ scores for this pair. |
Bochao Jia, Faming liangfmliang@purdue.edu
Liang, F., Song, Q. and Qiu, P. (2015). An Equivalent Measure of Partial Correlation Coefficients for High Dimensional Gaussian Graphical Models. J. Amer. Statist. Assoc., 110, 1248-1265.
Liang, F. and Zhang, J. (2008) Estimating FDR under general dependence using stochastic approximation. Biometrika, 95(4), 961-977.
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