Description Usage Arguments Value Author(s) See Also Examples

Refit the regressions given matrices of responses, predictors, and the coefficients/interactions matrix. This is typically used after the lasso, since the coefficients were shrinked.

1 | ```
lmMatrixFit(y, x = NULL, mat, th = NULL)
``` |

`y` |
Input response matrix, typically expression data with genes/variables in columns and samples/measurements in rows. Or when input x is NULL, y should be an object of two lists: y: expression data and x: copy number data |

`x` |
Input predictor matrix, typically copy number data, genes/predictors in columns and samples/measurements in rows. Can be NULL |

`mat` |
Coefficient matrix, number of columns is the number of predictors (y) and number of rows is the number of responses (x) |

`th` |
The threshold to use in order to determine which coefficients are non-zero, so the corresponding predictors are used |

`coefMat` |
A coefficient matrix, rows are responses and columns are predictors |

`resMat` |
A residual matrix, each row is the residuals of a response. |

`pvalMat` |
Matrix of p-values for each coefficients |

Yinyin Yuan

lm, matrixLasso

1 2 3 4 5 6 |

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