aux.biom {BioMark} | R Documentation |

## Auxiliary functions in the biomarker package

### Description

These functions return coefficient sizes for a variety of
modelling methods. Not to be called directly by the user - use function
`get.biom`

for that.

### Usage

```
pcr.coef(X, Y, ncomp, scale.p, ...)
pcr.stab(X, Y, ncomp, scale.p,
segments = NULL, variables = NULL, ...)
pls.coef(X, Y, ncomp, scale.p, ...)
pls.stab(X, Y, ncomp, scale.p,
segments = NULL, variables = NULL, ...)
vip.coef(X, Y, ncomp, scale.p, ...)
vip.stab(X, Y, ncomp, scale.p,
segments = NULL, variables = NULL, ...)
lasso.coef(X, Y, scale.p,
lasso.opt = biom.options()$lasso,...)
lasso.stab(X, Y, scale.p,
segments = NULL, variables = NULL, ...)
shrinkt.coef(X, Y, scale.p, ...)
shrinkt.stab(X, Y, scale.p,
segments = NULL, variables = NULL, ...)
studentt.coef(X, Y, scale.p, ...)
studentt.stab(X, Y, scale.p,
segments = NULL, variables = NULL, ...)
pval.pcr(X, Y, ncomp, scale.p, npermut)
pval.plsvip(X, Y, ncomp, scale.p, npermut, smethod)
```

### Arguments

`X` |
Data matrix. Usually the number of columns (variables) is (much) larger than the number of rows (samples). |

`Y` |
Class indication. Either a factor, or a numeric vector. |

`ncomp` |
Number of latent variables to use in PCR and PLS (VIP)
modelling. In function |

`scale.p` |
Scaling. This is performed individually in every crossvalidation iteration, and can have a profound effect on the results. Default: "none". Other possible choices: "auto" for autoscaling, "pareto" for pareto scaling, "log" and "sqrt" for log and square root scaling, respectively. |

`segments` |
matrix where each column indicates a set of samples to be left out of the analysis. |

`variables` |
indices of variables to be used in the analysis. |

`lasso.opt` |
optional arguments to the |

`...` |
Further arguments for modelling functions. Often used to catch unused arguments. |

`npermut` |
Number of permutations to use in the calculation of the p values. |

`smethod` |
Either "both", "pls", or "vip" - indicates what coefficients to convert to p values. Both are derived from PLS models so it is much more efficient to calculate them together. |

### Value

The functions ending in `coef`

return t-statistics or
model coefficients for all variables. The functions
ending in `stab`

return these statistics in a matrix, one column
per segment. The functions starting with `pval`

convert model
coefficients or VIP statistics into p values, using permutation
resampling.

### Author(s)

Ron Wehrens

### See Also

*BioMark*version 0.4.5 Index]