# Hidden F function for matrix data

### Description

Fits linear model to ymtx, a matrix of responses of dimension r-by-c. Constructs all possible configurations of rows into two non-empty groups, then, for each configuration, fits full factorial effects models with three factors for group, group-by-column, row and row nested within column. The maximum F-ratio for group-by-column interaction is reported along with Bonferroni-adjusted p-value.

### Usage

1 | ```
HiddenF(ymtx)
``` |

### Arguments

`ymtx` |
A matrix of responses, with rows corresponding to levels of one factor, and columns the levels of a second factor |

### Value

List-object of class ‘HiddenF’ with components

`adjpvalue` |
(Bonferroni-adjusted) pvalue from configuration with maximal hidden additivity |

`config.vector` |
Vector of group indicators for configuration with maximal hidden additivity |

`tall` |
A list with components y, row, col |

`cc` |
Number of possible configurations |

### Author(s)

Jason A. Osborne jaosborn@ncsu.edu, Christopher T. Franck and Bongseog Choi

### References

Franck CT, Nielsen, DM and Osborne, JA. (2013) A Method for Detecting Hidden Additivity in two-factor Unreplicated Experiments, Computational Statistics and Data Analysis, 67:95-104.

### See Also

`summary.HiddenF`

### Examples

1 2 3 4 | ```
library(hiddenf)
data(cjejuni.mtx)
cjejuni.out <- HiddenF(cjejuni.mtx)
summary(cjejuni.out)
``` |

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