Description Usage Arguments Value See Also Examples

Generate an expression from the probe

1 2 | ```
generateExprVal.method.farms(probes, weight, mu, cyc, tol, weighted.mean, robust, minNoise, correction, laplacian, centering, spuriousCorrelation, ...)
``` |

`probes` |
a matrix of probe intesities with rows representing
probes and columns representing
samples. Usually |

`weight` |
Hyperparameter value in the range of [0,1] which determines the influence of the prior. The default value is 0.5 |

`mu` |
Hyperparameter value which allows to quantify different aspects of potential prior knowledge. A value near zero assumes that most genes do not contain a signal, and introduces a bias for loading matrix elements near zero. Default value is 0 |

`cyc` |
Value which determinates the maximum numbers of EM-Steps. Default value is set to 30 |

`tol` |
Value which determinates the termination tolerance. Convergence threshold is set to 1E-05. |

`weighted.mean` |
Boolean flag, that indicates whether a weighted mean or a least square fit is used to summarize the loading matrix. The default value is set to FALSE. |

`robust` |
Boolean flag, that ensures non-constant results. Default value is TRUE. |

`minNoise` |
Value, minimal noise assumption. Default value is 0.0001. |

`correction` |
Value that indicates whether the covariance matrix should be corrected for negative eigenvalues which might emerge from the non-negative correlation constraints or not. Default = O (means that no correction is done), 1 (minimal noise (0.0001) is added to the diagonal elements of the covariance matrix to force positive definiteness), 2 (Maximum Likelihood solution to compute the nearest positive definite matrix under the given non-negative correlation constraints of the covariance matrix) |

`laplacian` |
Boolean flag, indicates whether a Laplacian prior for the factor is employed or not. Default value is FALSE. |

`centering` |
Indicates whether the data is "median" or "mean" centered. Default value is "median". |

`spuriousCorrelation` |
Numeric value in the range of [0,1] that quantifies the suppression of spurious correlation when using the Laplacian prior. Default value is 0 (no suppression). Note, that this parameter is only active when the laplacian parameter is set to TRUE. |

`...` |
extra arguments to pass to the respective function |

A list containing entries:

`exprs` |
The expression values. |

`se.exprs` |
Estimate of the hidden variable. |

`generateExprSet-methods`

,`generateExprVal.method.playerout`

,`li.wong`

, `medianpolish`

1 2 3 4 | ```
library(affy)
data(SpikeIn) ##SpikeIn is a ProbeSets
probes <- pm(SpikeIn)
exprs.farms <- generateExprVal.method.farms(probes)
``` |

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