getBlockCov | R Documentation |
Computes covariance matrix entries and associated alpha, beta
and gamma quantities defined in Aw, Spence and Song (2023),
for partitionable features that are grouped into blocks. Uses
precomputation to compute the unique entries of the asymptotic
covariance matrix of the pairwise Hamming distances in O(N^2)
time.
getBlockCov(X, block_boundaries, block_labels, p)
X |
The binary or real matrix |
block_boundaries |
Vector denoting the positions where a new block of non-independent features starts. |
block_labels |
Length |
p |
The power |
This is used in the large P
asymptotics of the permutation test.
Dependencies: buildReverse, getHammingDistance, getLpDistance
The three distinct entries of covariance matrix, (\alpha, \beta, \gamma)
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