Description Usage Arguments Value See Also

View source: R/zeitzeiger_cv.R

`zeitzeigerPredictCv`

calls `zeitzeigerPredict`

for each fold of cross-validation.
By default, if a parallel backend is registered, this function processes the folds in parallel.

1 2 3 |

`x` |
Matrix of measurements, observations in rows and features in columns. |

`time` |
Vector of values of the periodic variable for observations, where 0 corresponds to the lowest possible value and 1 corresponds to the highest possible value. |

`foldid` |
Vector of values indicating which fold each observation is in. |

`spcResultList` |
Result from |

`fitMeanArgs` |
List of arguments to pass to |

`constVar` |
Logical indicating whether to assume constant variance as a function of the periodic variable. |

`fitVarArgs` |
List of arguments to pass to |

`nSpc` |
Vector of the number of SPCs to use for prediction. If |

`betaSv` |
Logical indicating whether to use the singular values of the SPCs as weights in the likelihood calculation. |

`timeRange` |
Vector of values of the periodic variable at which to calculate likelihood. The time with the highest likelihood is used as the initial value for the MLE optimizer. |

`dopar` |
Logical indicating whether to process the folds in parallel.
Use |

A list of the same structure as `zeitzeigerPredict`

, combining the results
from each fold of cross-validation.

`timeDepLike` |
3-D array of likelihood, with dimensions for each observation,
each element of |

`mleFit` |
List (for each element in |

`timePred` |
Matrix of predicted times for observations by values of |

`zeitzeigerPredict`

, `zeitzeigerFitCv`

, `zeitzeigerSpcCv`

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