Description Usage Arguments Value Author(s) References Examples
Simulate compeletely missing at random (CMAR) data with a band structure, which can be used in GraphIRO(data,...)
for estimating the structure of the Gaussian graphical network.
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n |
Number of observations, default of 200. |
p |
Number of covariates, default of 100. |
type |
C_{i,j}=≤ft\{\begin{array}{ll} 0.5,&\textrm{if $≤ft| j-i \right|=1, i=2,...,(p-1),$}\\ 0.25,&\textrm{if $≤ft| j-i \right|=2, i=3,...,(p-2),$}\\ 1,&\textrm{if $i=j, i=1,...,p,$}\\ 0,&\textrm{otherwise.} \end{array}\right. |
rate |
Missing rate, the default value is 0.1. |
data |
nxp Gaussian distributed data with missing. |
A |
pxp adjacency matrix used for generating data. |
Bochao Jiajbc409@gmail.com and Faming Liang
Liang, F., Jia, B., Xue, J., Li, Q., and Luo, Y. (2018). An Imputation Regularized Optimization Algorithm for High-Dimensional Missing Data Problems and Beyond. Submitted to Journal of the Royal Statistical Society Series B.
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