Description Usage Arguments Value Author(s) References Examples
Simulate incomplete data for highdimensional linear regression with dependent or independent covariatesRegICRO(x,y...)
.
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n 
Number of observations, default of 100. 
p 
Number of covariates, default of 200. 
coef 
A px1 vector of coefficients for the linear regression model. The intercept coefficient is default to 1. 
data.type 
When 
miss.type 

rate 
Missing rate, the default value is 0.1. 
x 
nxp covariates matrix. 
y 
nx1 responses. 
coef 
px1 vector of coefficients for the linear regression model. 
Bochao Jiajbc409@ufl.edu and Faming Liang
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, 12481265.
Liang, F. and Zhang, J. (2008) Estimating FDR under general dependence using stochastic approximation. Biometrika, 95(4), 961977.
Liang, F., Jia, B., Xue, J., Li, Q., and Luo, Y. (2018). An Imputation Regularized Optimization Algorithm for HighDimensional Missing Data Problems and Beyond. Submitted to Journal of the Royal Statistical Society Series B.
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