This is an internal function contained in the multiFAMM function. This step uses the information from the univariate FLMMs for the MFPCA. It also allows a simple weighting scheme of the MFPCA.

1 | ```
prepare_mfpca(model_list, fRI_B, mfpc_weight)
``` |

`model_list` |
List containing sparseFLMM objects for each dimension as given by the output of apply_sparseFLMM() |

`fRI_B` |
Boolean for including functional random intercept for individual
(B in Cederbaum). Defaults to |

`mfpc_weight` |
TRUE if the estimated univariate error variance is to be used as weights in the scalar product of the MFPCA. |

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