Description Usage Arguments Value Author(s) Examples

View source: R/summarizeFarmsGaussian.R

This function runs the FARMS algorithm.

1 2 3 | ```
summarizeFarmsGaussian(probes, weight = 0.15, mu = 0, cyc = 10,
tol = 1e-04, weightType = "mean", init = 0.6, correction = 0,
minNoise = 0.35, centering = "median", refIdx)
``` |

`probes` |
A matrix with numeric values. |

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

`mu` |
Hyperparameter value which allows to quantify different aspects of potential prior knowledge. Values 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` |
Number of cycles for the EM algorithm. |

`tol` |
States the termination tolerance. Default is 0.00001. |

`weightType` |
Flag, that is used to summarize the loading matrix. The default value is set to mean. |

`init` |
Parameter for estimation. |

`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) |

`minNoise` |
States the minimal noise. Default is 0.35. |

`centering` |
States how the data is centered. Default is median. |

`refIdx` |
index or indices which are used for computation of the centering |

A list containing the results of the run.

Djork-Arne Clevert [email protected] and Andreas Mitterecker [email protected]

1 2 | ```
x <- matrix(rnorm(100, 11), 20, 5)
summarizeFarmsGaussian(x)
``` |

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