Description Usage Arguments Details Value

View source: R/getWeightMatrix.R

Initially, a weight is computed for each model and byKey. However, some models are not valid for some observations (as certain models are limited in how far they can extrapolate outside the range of the data). Thus, the final weight for each ensemble model at each observation will depend on that models performance for that byKey group as well as if that model is valid at that point.

1 | ```
getWeightMatrix(data, w, imputationParameters)
``` |

`data` |
The data.table containing the data. |

`w` |
The weights data.table, typically as produced in computeEnsembleWeight. There should be three columns: byKey, model, and weight. Weight gives the model weight for model within the byKey group, and exactly one row should exist for each byKey/model pair. |

`imputationParameters` |
A list of the parameters for the imputation algorithms. See defaultImputationParameters() for a starting point. |

This function creates a weight matrix to use in constructing the final ensemble. If F is a nxk matrix (n = number of observations, k = number of models) containing the fitted models, then this function constructs W, another nxk matrix of weights. The final ensemble estimate for observation i can be computed by sum(F[i,]*W[i,]).

A list of two objects. The first is a matrix of weights that can be multiplied by the fitted models to give the imputed values. Rows corresponding to non-missing values in data have values of NA. The second object is a matrix of errors for each model and each byKey. These error values are used for creating an estimate for the variability of each imputed value.

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