Description Usage Arguments Value

Main DataRemix function

1 2 3 |

`svdres` |
The full SVD decomposition of input gene expression profile X, which is equal to svd(X) |

`fn` |
The custom function which takes svdres and some additional custom parameters as input and output the biological metric to be maximized. The output of fn() can be a vector with multiple objective values and the objective to be maximized should be the last element of the vector |

`k_limits` |
The lower and upper bound of k. By default the lower bound is set to be 1 and the upper bound is set to be the half of the rank |

`p_limits` |
The lower and upper bound of p. By default the lower bound is set to be -1 and the upper bound is set to be 1 |

`mu_limits` |
The lower and upper bound of |

`num_of_initialization` |
By default it uses 5 steps of Random Search to initialize the Thompson Sampling. We also provide a coarsed grid option for initialization with num_of_initialization set to be 0 |

`num_of_thompson` |
The number of steps of Thompson Sampling, which is 600 by default |

`basis` |
The default mt is set to be 2,500. You can specify a smaller mt by using omega[1:2000,] for example, if you want to set mt to be 2,000 |

`xi` |
A pre-defined probability which ensures the search doesn't stuck in the local optimum, which is 0.1 by default |

`full` |
If full is set to be True, the output will be the complete search history. Otherwise the output will only be the optimal combination of k, p and |

`verbose` |
If verbose is set to be True, then after each Thompson Sampling iteration, the function will print out the intermediate result |

`...` |
Additional arguments used as inputs to fn() |

`para` |
If verbose is set to be True, the dimension of para is (num_of_initialization+num_of_thompson)-by-4(k, p, |

`full` |
If verbose is set to be True, the dimension of full is (num_of_initialization+num_of_thompson)-by-(k, p, |

wgmao/DataRemix documentation built on Aug. 27, 2018, 5:08 p.m.

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