Description Usage Arguments Value Author(s) References

Permute the design matrix so that it is approximately correlated with the surrogate variables.

1 2 3 4 5 6 | ```
permute_design(
design_perm,
sv,
target_cor,
method = c("optmatch", "hungarian", "marriage")
)
``` |

`design_perm` |
A numeric design matrix whose rows are to be permuted
(thus controlling the amount by which they are correlated with the
surrogate variables). The rows index the samples and the columns index
the variables. The intercept should |

`sv` |
A matrix of surrogate variables |

`target_cor` |
A numeric matrix of target correlations between the
variables in |

`method` |
Should we use the optimal matching technique from Hansen and
Klopfer (2006) ( |

A list with two elements:

`design_perm`

A row-permuted version of the user-provided

`design_perm`

.`latent_var`

A matrix of the latent variables on which

`design_perm`

was matched.

David Gerard

Hansen, Ben B., and Stephanie Olsen Klopfer. "Optimal full matching and related designs via network flows." Journal of computational and Graphical Statistics 15, no. 3 (2006): 609-627.

Gale, David, and Lloyd S. Shapley. "College admissions and the stability of marriage." The American Mathematical Monthly 69, no. 1 (1962): 9-15.

C. Papadimitriou and K. Steiglitz (1982), Combinatorial Optimization: Algorithms and Complexity. Englewood Cliffs: Prentice Hall.

Hornik K (2005). "A CLUE for CLUster Ensembles." Journal of Statistical Software, 14(12). doi: 10.18637/jss.v014.i12

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