Build_JTree(C, cc, maxlev, whichsave)nrow(X)-1.maxlev, for which you want to save the basis functions and the covariance matrix.maxlev x 2. Each row records which two nodes/clusters of the tree were combined at each step in its construction.maxlev elements, where each element is a 2x2 Jacobi rotation matrix for each step of the treelet algorithm.maxlev x 2, where each row is a permutation of $(1,2)$ indicating which of the two nodes/clusters merged at that step is the sum variable (value of 1) and which is the difference (value of 2).maxlev x nrow(X) giving node/cluster labels at each step of the treelet algorithm. A label of zero indicates a node/cluster that was merged with another node/cluster and was the difference variable.maxlev elements. Only those elements that are specified in the whichsave argument will be non-null entries in the list. For the non-null entries, this is the covariance matrix calculated at that level of the tree. The covariances in this matrix are those between the weights (orthogonal projections onto local basis vectors) in the basis expansion of the data vector.Lee, AB, Nadler, B, Wasserman, L (2008). Treelets - an adaptive multi-scale basis for sparse unordered data. The Annals of Applied Statistics 2: 435-471.
Run_JTree, JTree_Basis, TCS