The (differential) entropy of a high-dimensional multivariate random variable is estimated from a (high-dimensional matrix) under a normality or k-NN distributional assumption.
Usage
hdEntropy(Y, method = "normal", k = 1, center = TRUE, indKnn = TRUE)
Arguments
Y
(High-dimensional) matrix. Rows are assumed to represent the samples, and columns represent the samples' genes or traits.
method
Distributional assumption under which entropy is to be estimated.
k
k-nearest neighbor parameter.
center
Logical indicator: should the columns of Y be centered around zero?
indKnn
Logical indicator: should samples' individual contributions to the k-NN entropy be reported?
Value
The entropy estimate is returned as a numeric.
References
Van Wieringen, W.N., Van der Vaart, A.W. (2011), "Statistical analysis of the cancer cell's molecular entropy using high-throughput data", Bioinformatics, 27(4), 556-563.