Description Usage Arguments Value See Also

View source: R/zeitzeiger_group.R

`zeitzeigerPredictGroup`

predicts the value of the periodic variable
for each group of test observations, where the amount of time between each
observation in a group is known. This function calls `bbmle::mle2`

.

1 2 3 4 |

`xTrain` |
Matrix of measurements for training data, observations in rows and features in columns. |

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

`xTest` |
Matrix of measurements for test data, observations in rows and features in columns. |

`groupTest` |
data.frame with one row per observation in |

`spcResult` |
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. |

A list with the following elements, where the groups will be sorted by their names.

`timeDepLike` |
3-D array of likelihood, with dimensions for each group of test observations,
each element of |

`mleFit` |
List (for each element in |

`timePred` |
Matrix of predicted times for each group of test observations by values of |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.