hdEntropy {sigaR} | R Documentation |
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.
hdEntropy(Y, method = "normal", k = 1, center = TRUE, indKnn = TRUE)
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? |
The entropy estimate is returned as a numeric
.
Wessel N. van Wieringen: w.vanwieringen@vumc.nl
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.
data(pollackGE16) hdEntropy(t(exprs(pollackGE16)), method="knn")