Generate precision matrix of triangle graph (chain like network) following the setup in Fan et al. (2009).
1  ChainOmega(p, sd = 1, norm.type = 2)

p 
dimension of generated precision matrix. 
sd 
seed for random number generation, default is 1. 
norm.type 
normalization methods of generated precision matrix, i.e., Ω_{11}=1 if norm.type = 1 and Ω_F =1 if norm.type = 2. Default value is 2. 
This function first construct a covariance matrix Σ that its (i,j) entry is exp (  h_i  h_j  / 2) with h_1 < h_2 < … < h_p. The difference h_i  h_{i+1} is generated i.i.d. from Unif(0.5,1). See Fan et al. (2009) for more details.
A precision matrix generated from triangle graph.
Will Wei Sun, Zhaoran Wang, Xiang Lyu, Han Liu, Guang Cheng.
NeighborOmega
1 2 3 4 5 6 7 8 9 
Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.
All documentation is copyright its authors; we didn't write any of that.