Description Usage Arguments Details Value Author(s) References See Also Examples

This function thresholds values in the treelet estimated covariance and returns a smoothed estimate of a covariance matrix.

1 |

`basis` |
the orthonormal treelet basis calculated at a specific level |

`cov` |
the corresponding covariance matrix calculated at level |

`lambda` |
a positive thresholding coefficient. Any element of the matrix |

This function implements the TCS method presented in the Crossett et al arXiv paper. The arguments `basis`

and `cov`

should be obtained from the `Run_JTree`

function. The `TCS`

function is written so that it does not calculate the treelet basis within the function but asks for it as an argument so that the subsampling method presented in the arXiv paper, or another method to obtain a reasonable value of lambda, can be implemented.

`smooth` |
the smoothed estimate of the covariance matrix. |

Trent Gaugler [email protected]

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. http://www.stat.cmu.edu/~annlee/AOAS137.pdf

`Build_JTree`

, `JTree_Basis`

, `Run_JTree`

1 2 3 4 5 6 7 8 9 10 11 | ```
data(Ahat)
out=Run_JTree(Ahat,49,49)
basis=out$basis[[49]]
cov=out$TreeCovs[[49]]
temp=TCS(basis,cov,.04)
#The value .04 above is arbitrary, and the user
#should carefully select this value. One approach
#is the subsampling method outlined in the Crossett et al
#arXiv paper. The value in 'temp' is the smoothed estimate
#of the relationship matrix.
``` |

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