divide.sdp

<p>Approximate a covariance matrix by a block diagonal matrix with blocks
of approximately equal size using Ward's method for hierarchical clustering</p>

internal

The knockoff filter is a general procedure for controlling the false discovery rate (FDR)
when performing variable selection.
For more information, see the website below and the accompanying paper: Candes et al.,
"Panning for gold: model-X knockoffs for high-dimensional controlled variable selection",
J. R. Statist. Soc. B (2018) 80, 3, pp. 551-577.

Matteo Sesia

knockoff

The Knockoff Filter for Controlled Variable Selection

Rina Foygel Barber

Emmanuel Candes

Lucas Janson

Evan Patterson

divide.sdp function

Approximate a covariance matrix by a block diagonal matrix with blocks
of approximately equal size using Ward's method for hierarchical clustering — divide.sdp

Approximate a covariance matrix by a block diagonal matrix with blocks
of approximately equal size using Ward's method for hierarchical clustering

divide.sdp: Approximate a covariance matrix by a block diagonal matrix with blocks of approximately equal size using Ward's method for hierarchical clustering

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