Description Usage Arguments Details Value Author(s) See Also Examples
Generate observations from separable tensor normal distribution.
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n |
number of generated observations. |
m.vec |
vector of tensor mode dimensions, e.g., |
mu |
array of mean for tensor normal distribution with dimension |
Sigma.list |
list of covariance matrices in mode sequence. Default is |
type |
type of precision matrix, default is 'Chain'. Optional values are 'Chain' for
triangle graph and 'Neighbor' for nearest-neighbor graph. Useless if |
sd |
seed of random number generation, default is 1. |
knn |
sparsity of precision matrix, i.e., matrix is generated from a |
norm.type |
normalization method of 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 generates obeservations from separable tensor normal distribution and returns a m1 * ... * mK * n
array.
If Sigma.list
is not given, default distribution is from either triangle graph or nearest-neighbor graph (depends on type
).
An array with dimension m_1 * ... * m_K * n.
Xiang Lyu, Will Wei Sun, Zhaoran Wang, Han Liu, Jian Yang, Guang Cheng.
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