permute_design | R Documentation |

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

```
permute_design(
design_perm,
sv,
target_cor,
method = c("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 Gale-Shapley algorithm
for stable marriages ( |

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

Gale, David, and Lloyd S. Shapley. "College admissions and the stability of marriage."

*The American Mathematical Monthly*69, no. 1 (1962): 9-15. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/00029890.1962.11989827")}.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). \Sexpr[results=rd]{tools:::Rd_expr_doi("10.18637/jss.v014.i12")}. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.18637/jss.v014.i12")}.

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